semanticRelation; // keyword info matched in the
search
} | |
+
+| | |
+|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|-------------|
+| } DOC_RESULT_STRUCT; //Primary Search integration typedef struct { string query; // // save the search result // vector<DOC_RESULT_STRUCT> doc_result_list; // to store doc search results vector<DOC_RESULT_STRUCT> def_result_list; // to store definition search results vector<DOC_RESULT_STRUCT> sec_result_list; // to store section search results vector<DOC_RESULT_STRUCT> psg_result_list; // to store paragraph search results } doc_result; | |
+| Member Variables | //Skipped// |
+| Member Functions | |
+| void hexconvert( char *text, unsigned char bytes[] ); string replaceAll(string str, string pattern, string replace); string* strSplit(string strOrigin, string strTok); PrimarySearch(string solrIP, string hbaseIP, string jarPath); string p_q_generation(string collectionName, N_Doc ndoc); string p_q_reGeneration(string collectionName, N_Doc ndoc, vector<string> candidateAnswer); string p_q_reGeneration(string collectionName, N_Doc ndoc, string docid_sentid); vector<string> assignPassageRange(string docid_sentid, int range); PrimarySearch(); ~PrimarySearch(); string p_search( string collectionName, string query, int max_cnt); string p_search( string collectionName, string query, string title, int max_cnt); string getLang(string collectionName, string rowkey); string getRowkey(string docid);
| |
+
+#### A.2.2 Class\_API for candidate answer generation sub-block
+
+This clause provides information for the Class\_API for candidate answer generation sub-block.
+
+| | |
+|-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|--|
+| Class Name | |
+| AnswerUnit | |
+| Description | |
+| Answer candidates and structure of representing evidences | |
+| Include files | |
+| class AnswerUnit { public: string answer; string answer_key; // double tot_weight; //engine matching weight (normalized reliability) int total_sent; | |
+
+```
+
+ list answer_sent;
+ CIFeature ci_feat; //context independent features
+};
+
+class AnswerFeature
+{
+public:
+
+ AnswerFeature(void);
+ ~AnswerFeature(void);
+
+ double TyCor_score; //TyCor feature
+ double Ln_score; //IR+ voc similarity feature
+ double SEM_score; //syntax and meaning feature
+ double CONS_score; //question constraint feature
+
+ double IR_score; //IRweight
+
+ string TE; //integration
+
+ double confidence; //answer confidence
+
+ string src_ENGINE; // source of engine
+};
+
+// answer candidate sentences for Answer Evidence
+class AnswerSent
+{
+public:
+ string answer;
+ double weight;
+
+ string docID; //answer doc ID
+ int sentID; //answer sentence ID
+ QADocType doc_type; //
+
+ //canGen results
+ string source; // source (Content, Title, ...)
+ double DIRweight; // doc search weight
+ int DIRsrcType; // 0=Doc, 1=section, 2=sentence
+
+ string title;
+ string sent;
+ string url;
+ string cpname;
+ unsigned long long date=0;
+};
+
+//context independent features
+class CIFeature
+{
+public:
+ string type; // types
+ string NEType; // NE type
+ double inQ = 0; // if included in question
+
+ double CIweight; //after feature engineering
+ double TyCor_vec[TyCor_vec_SIZE];
+
+ string CI_feature; //CI feature for training str
+};
+
+```
+
+| | |
+|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|--|
+| Class Name | |
+| CandidateGenerator | |
+| Description | |
+| Top class for answer candidate generation | |
+| Include files | |
+| #include "DR/DR.h" #include "QStruct.h" #include "DBSolution/DBSolution.h" #include "GetNDocHeader/GetNDoc.h" #include "TyCor/TyCor.h" #include "LingCor/LingCor.h" #include "SpaTempCor/SpaTempCor.h" #include "set" typedef struct CandidateAnswer { string text; // text of candidate answers string type; // type of candidate answers (NE, NP, ...) string NEType; // NE type string source; // source (Content, Title, ...) string sentenceText; // text of the sentence string docID; // extracted document ID string paraID; // extracted paragraph ID int sentenceID = -1; // extracted sentence ID int beginMorpID = -1; // starting morpheme ID int endMorpID = -1; // last morpheme ID int beginWordID = -1; // starting word ID int endWordID = -1; // last word ID LATScore LATScr; // LAT similarity SATScore SATScr; // SAT similarity SpaceScore spaceScr; // space similarity TimeScore timeScr; // time similarity LingScore lingScr; // context similarity string dependency; // used in TE } CandidateAnswer; typedef struct CandidateAnswerConfig { bool SUPPORT_PASSAGE_SEARCH=false; bool EXTRACT_NE=false; bool EXTRACT_NP=false; bool USE_LAT_SCORE=false; bool USE_SAT_SCORE=false; bool USE_SPACE_SCORE=false; bool USE_TIME_SCORE=false; bool USE_WORD_SCORE=false; bool USE_WORD_BI_SCORE=false; bool USE_WORD_ORDER_SCORE=false; bool USE_SYN_SCORE=false; bool VERBOSE_Q_LAT=false; bool VERBOSE_Q_DEPENDENCY=false; bool VERBOSE_DOCS_DEPENDENCY=false; bool VERBOSE_SYN_SCORE=false; } CandidateAnswerConfig; typedef pair<int,int> CandidateAnswerId; | |
+| Member Variables | |
+| DBSolution *dbSol; string dbPath; CGetNDoc getNDoc; TyCor tyCor; LingCor lingCor;
| |
+
+| |
+|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+| SpaTempCor spaTempCor; CandidateAnswerConfig config;
|
+| Member Functions |
+| CandidateGenerator(); bool initialize( string rscDir, DBSolution *dbSol, string dbPath, Searcher *kornetSearcher=NULL ); vector<CandidateAnswer> generateCandAns( QDecomp_Info& q, doc_result& dr ); static void printCandidateAnswers( vector<CandidateAnswer>& cands ); static void printCandidateAnswer( CandidateAnswer& cand, int index=-1 );
|
+
+| |
+|-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+| Class Name |
+| AnswerHypo |
+| Description |
+| Extraction of answer candidate and hypothesis generation according to the questions |
+| Include files |
+| #include "math.h" #include "QAConfig.h" #include "AnswerType.h" //=====Question analysis #include "QStruct.h" #include "QAnalHeader/QAnalyzer.h" #include "QAJsonHeader/QAnalJsonRW.h" //===== document search #include "PrimarySearch/PrimarySearch.h" #include "QAJsonHeader/DocResultParser.h" //===== candidate answer generation #include "CanGen/CanGenerator.h" #include "CI/TypeCor.h" /*===== KB search #include "KBInterface/KBInterface.h" //===== real time extraction of candidate answers #include "CanGen/CandidateGenerator.h" /**/ /*****/ //for multi-thread extern CQAnalRSCMng * qResourceMng; // extern Dictionary * gkornet; //lexical semantic concept network extern map<int, string> *ExAtMap; extern map<string, int> *rExAtMap; extern QAConfig QAConfig_core;
|
+| Member Variables |
+| QAnal_Result Q; //question analysis result structure CQAnalJsonRW * QJsonRW; // question analyzer JsonRW //Primary Search----- PrimarySearch * ps; DocResultParser *DocJsonRW; double DIR_top_weight; //anwer candidate extraction----- float CONF_CUT_OFF; CanGenerator * CanGen; TypeCor * CI;
|
+
+##### **Member Functions**
+
+```
+
+ //real time candidate answer extraction
+ int get_answerCandidate_fromIR(string Q_json, int subQ_idx, doc_result
+ lvResult, list & RES);
+ //subQ question merge
+ bool merge_answerCandidate_fromSubQ(vector
+ sub_AnsCan_vec, int subQ_idx, map & AnsUnit_map);
+ //pre_softfilter
+ int pre_soft_filter(CandidateAnswer & AnsCan, int subQ_idx);
+
+```
+
+###### **Function Name**
+
+get\_answerCandidate\_fromIR
+
+Class Name
+
+AnswerHypo
+
+Description
+
+Candidate answer generation based on document search
+
+Syntax
+
+```
+
+int get_answerCandidate_fromIR(string Q_json, int subQ_idx, doc_result
+lvResult, list & RES);
+
+```
+
+Return Value
+
+```
+
+return int; // number of candidate answers
+list RES : //candidate answer list basically ordered
+
+```
+
+Parameters
+
+```
+
+string input_Json //result json (with "||" division)
+int subQ_idx: // processed question index (-1: original question)
+
+```
+
+##### **Function Name**
+
+pre\_soft\_filter
+
+Class Name
+
+AnswerHypo
+
+Description
+
+Filtering function for the answer candidates as the doc search results
+
+Syntax
+
+```
+
+int pre_soft_filter(CandidateAnswer & AnsCan, int subQ_idx);
+
+```
+
+Return Value
+
+```
+
+return int; //if filtering applied
+0: not object for filtering
+1: if more than 1, filtering should be applied
+
+```
+
+Parameters
+
+```
+
+CandidateAnswer & AnsCan // individual answer candidate
+int subQ_idx: (processed question) index (-1: original question)
+
+```
+
+### A.3 Class API for answer inference/generation
+
+This clause provides information for the class API for answer inference/generation.
+
+| | |
+|------------------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+| Class Name | |
+| AnswerConfidence | |
+| Description | Among answer candidates from different answer generation module, to select the answer candidate with the highest reliability and to verify the answer to the question. |
+| Include files | #if !defined(AFX_ANSWERRANK_H__C4797D53_04A5_4E4E_BE8F_841D4BC76032__INCLUDED_) #define AFX_ANSWERRANK_H__C4797D53_04A5_4E4E_BE8F_841D4BC76032__INCLUDED_ #if _MSC_VER > 1000 #pragma once #endif // _MSC_VER > 1000 #define INDI_MAX 30 #include "QAConfig.h"
|
+| Member Variables | xmlrpc_c::clientSimple myClient; /// Object pointer of QAConfiging for answer inference resource loading and reliability model loading QAConfig *qconfig; Merge * AnsMerge; /// answer filtering vector vector<string> except_answer; /// answer candidates integration exception rules vector<string> except_is_redirect_rule; /// answer filtering rule map map<string, string> filter_map; /// answer filtering rule map using LAT and SAT map<string, string> latsat_filter_map;
|
+| Member Functions | public: AnswerRank(); virtual ~AnswerRank(); void ARank_THREAD_init(); string soft_filter_4UIMA(string json_in); string answer_merge_4UIMA(string json_in); private: xmlrpc_c::clientSimple myClient; QAConfig *qconfig; /// Merge object pointer for answer candidates integration Merge * AnsMerge; /// answer filtering vector vector<string> except_answer; /// space information NE vector vector<string> space; /// time information NE vector vector<string> time; map<string, string> filter_map; map<string, string> latsat_filter_map;
|
+
+```
+
+ bool latsat_filter(string NE_Type, map & latsat_filter_map,
+vector latVec, string first_SAT, double KB_score, bool q_type);
+ bool answer_filter(string NE_Type, map & filter_map, string
+SAT_Type);
+ bool answer_filter_lat(string NE_Type, vector latVec, bool
+q_type);
+ bool soft_filter_lat(string candidate, string NE_Type, string SAT_Type,
+vector latVec, double KB_score, bool q_type, string first_SAT);
+ bool soft_filter_sat(string candidate, string NE_Type, string SAT_Type,
+vector latVec, double KB_score, bool q_type, string first_SAT);
+ bool soft_filter_string(string candidate, string NE_Type, vector
+latVec, string question, double KB_score, bool q_type);
+ bool update_resource();
+ bool except_one_char_answer(string & answer, string & taggedQ, QAnal_Result
+Q);
+ string make_feature(list::iterator lpAu, int rank);
+ double conf_wiseqa(int blank_size, string answer_type, int q_exam_size,
+list::iterator lpAu, bool lat_flag, bool sat_flag, string q_type, int
+rank, string SAT_CONF_TYPE);
+ double conf_all(int blank_size, string answer_type, int q_exam_size,
+list::iterator lpAu, string q_type, int rank, string SAT_CONF_TYPE);
+ /** Reliability calculation */
+ bool overlap_question(vector vec, string taggedQ, string question,
+QAnal_Result Q);
+ /** final answer inference */
+ int re_ranking_answerCandidate(list & RES, int mode, bool
+select, int select_size, bool negation, bool lat_flag, bool sat_flag, string
+qstring, string SAT_Type, QAnal_Result Q, string q_type, string SAT_CONF_TYPE,
+string first_SAT);
+ bool exist_kb_AnswerUnit(list & RES, string json);
+ double thre_type(string conf_type, bool lat, bool sat); //threshold measure
+
+```
+
+
+
+
+
+## SERIES OF ITU-T RECOMMENDATIONS
+
+| | |
+|-----------------|-----------------------------------------------------------------------------------------------------------------------------------------------------------|
+| Series A | Organization of the work of ITU-T |
+| Series D | Tariff and accounting principles and international telecommunication/ICT economic and policy issues |
+| Series E | Overall network operation, telephone service, service operation and human factors |
+| Series F | Non-telephone telecommunication services |
+| Series G | Transmission systems and media, digital systems and networks |
+| Series H | Audiovisual and multimedia systems |
+| Series I | Integrated services digital network |
+| Series J | Cable networks and transmission of television, sound programme and other multimedia signals |
+| Series K | Protection against interference |
+| Series L | Environment and ICTs, climate change, e-waste, energy efficiency; construction, installation and protection of cables and other elements of outside plant |
+| Series M | Telecommunication management, including TMN and network maintenance |
+| Series N | Maintenance: international sound programme and television transmission circuits |
+| Series O | Specifications of measuring equipment |
+| Series P | Telephone transmission quality, telephone installations, local line networks |
+| Series Q | Switching and signalling, and associated measurements and tests |
+| Series R | Telegraph transmission |
+| Series S | Telegraph services terminal equipment |
+| Series T | Terminals for telematic services |
+| Series U | Telegraph switching |
+| Series V | Data communication over the telephone network |
+| Series X | Data networks, open system communications and security |
+| Series Y | Global information infrastructure, Internet protocol aspects, next-generation networks, Internet of Things and smart cities |
+| Series Z | Languages and general software aspects for telecommunication systems |
\ No newline at end of file
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+
+
+International Telecommunication Union
+
+**ITU-T**
+
+TELECOMMUNICATION
+STANDARDIZATION SECTOR
+OF ITU
+
+**F.746.12**
+
+(03/2022)
+
+SERIES F: NON-TELEPHONE TELECOMMUNICATION
+SERVICES
+
+Multimedia services
+
+---
+
+**Requirements for a real-time interactive
+multimedia service under poor network
+conditions**
+
+Recommendation ITU-T F.746.12
+
+ITU-T
+
+
+
+The logo of the International Telecommunication Union (ITU) is located in the bottom right corner. It features a blue globe with a white grid pattern, overlaid by a stylized 'ITU' text in blue.
+
+ITU logo
+
+# ITU-T F-SERIES RECOMMENDATIONS **NON-TELEPHONE TELECOMMUNICATION SERVICES**
+
+| | |
+|-----------------------------------------------------------------|--------------------|
+| TELEGRAPH SERVICE | |
+| Operating methods for the international public telegram service | F.1–F.19 |
+| The gentex network | F.20–F.29 |
+| Message switching | F.30–F.39 |
+| The international telemessage service | F.40–F.58 |
+| The international telex service | F.59–F.89 |
+| Statistics and publications on international telegraph services | F.90–F.99 |
+| Scheduled and leased communication services | F.100–F.104 |
+| Phototelegraph service | F.105–F.109 |
+| MOBILE SERVICE | |
+| Mobile services and multdestination satellite services | F.110–F.159 |
+| TELEMATIC SERVICES | |
+| Public facsimile service | F.160–F.199 |
+| Teletex service | F.200–F.299 |
+| Videotex service | F.300–F.349 |
+| General provisions for telematic services | F.350–F.399 |
+| MESSAGE HANDLING SERVICES | F.400–F.499 |
+| DIRECTORY SERVICES | F.500–F.549 |
+| DOCUMENT COMMUNICATION | |
+| Document communication | F.550–F.579 |
+| Programming communication interfaces | F.580–F.599 |
+| DATA TRANSMISSION SERVICES | F.600–F.699 |
+| MULTIMEDIA SERVICES | F.700–F.799 |
+| ISDN SERVICES | F.800–F.849 |
+| UNIVERSAL PERSONAL TELECOMMUNICATION | F.850–F.899 |
+| ACCESSIBILITY AND HUMAN FACTORS | F.900–F.999 |
+
+*For further details, please refer to the list of ITU-T Recommendations.*
+
+# Recommendation ITU-T F.746.12
+
+# Requirements for a real-time interactive multimedia service under poor network conditions
+
+## Summary
+
+Recommendation ITU-T F.746.12 describes the scenarios, general framework and requirements for a real-time interactive multimedia service (RIMS) under poor network conditions. The RIMS system plays an important role in many scenarios and situations, e.g., emergency relief, remote education and emergency communication. The RIMS requires provision of measures for dynamic adjustment of coding parameters, including those for video and audio coding, and it requires setting maximal priority of audio communication under low-speed network conditions and configuring usage attributes to ensure the appropriate priority from high to low of service uses.
+
+## History
+
+| Edition | Recommendation | Approval | Study Group | Unique ID* |
+|---------|----------------|------------|-------------|---------------------------------------------------------------------------|
+| 1.0 | ITU-T F.746.12 | 2022-03-16 | 16 | 11.1002/1000/14959 |
+
+## Keywords
+
+Multimedia service, poor network conditions, real-time.
+
+---
+
+\* To access the Recommendation, type the URL in the address field of your web browser, followed by the Recommendation's unique ID. For example, .
+
+## FOREWORD
+
+The International Telecommunication Union (ITU) is the United Nations specialized agency in the field of telecommunications, information and communication technologies (ICTs). The ITU Telecommunication Standardization Sector (ITU-T) is a permanent organ of ITU. ITU-T is responsible for studying technical, operating and tariff questions and issuing Recommendations on them with a view to standardizing telecommunications on a worldwide basis.
+
+The World Telecommunication Standardization Assembly (WTSA), which meets every four years, establishes the topics for study by the ITU-T study groups which, in turn, produce Recommendations on these topics.
+
+The approval of ITU-T Recommendations is covered by the procedure laid down in WTSA Resolution 1.
+
+In some areas of information technology which fall within ITU-T's purview, the necessary standards are prepared on a collaborative basis with ISO and IEC.
+
+## NOTE
+
+In this Recommendation, the expression "Administration" is used for conciseness to indicate both a telecommunication administration and a recognized operating agency.
+
+Compliance with this Recommendation is voluntary. However, the Recommendation may contain certain mandatory provisions (to ensure, e.g., interoperability or applicability) and compliance with the Recommendation is achieved when all of these mandatory provisions are met. The words "shall" or some other obligatory language such as "must" and the negative equivalents are used to express requirements. The use of such words does not suggest that compliance with the Recommendation is required of any party.
+
+## INTELLECTUAL PROPERTY RIGHTS
+
+ITU draws attention to the possibility that the practice or implementation of this Recommendation may involve the use of a claimed Intellectual Property Right. ITU takes no position concerning the evidence, validity or applicability of claimed Intellectual Property Rights, whether asserted by ITU members or others outside of the Recommendation development process.
+
+As of the date of approval of this Recommendation, ITU had not received notice of intellectual property, protected by patents/software copyrights, which may be required to implement this Recommendation. However, implementers are cautioned that this may not represent the latest information and are therefore strongly urged to consult the appropriate ITU-T databases available via the ITU-T website at .
+
+© ITU 2022
+
+All rights reserved. No part of this publication may be reproduced, by any means whatsoever, without the prior written permission of ITU.
+
+## Table of Contents
+
+###### Page
+
+| | | |
+|------------|--------------------------------------------------------------------------------------|----|
+| 1 | Scope ..... | 1 |
+| 2 | References..... | 1 |
+| 3 | Definitions ..... | 1 |
+| 3.1 | Terms defined elsewhere ..... | 1 |
+| 3.2 | Terms defined in this Recommendation..... | 1 |
+| 4 | Abbreviations..... | 2 |
+| 5 | Convention..... | 2 |
+| 6 | Overview ..... | 2 |
+| 7 | Key components of a real-time interactive multimedia service system ..... | 3 |
+| 8 | Requirements for real-time interactive multimedia service system ..... | 4 |
+| 8.1 | General requirements..... | 4 |
+| 8.2 | Requirements for application service unit..... | 4 |
+| 8.3 | Requirements for application client..... | 5 |
+| 8.4 | Requirements for call control service unit..... | 5 |
+| 8.5 | Requirements for media processing service unit..... | 5 |
+| 8.6 | Requirements for media storage service unit ..... | 5 |
+| 8.7 | Requirements for directory server ..... | 5 |
+| 8.8 | Requirements for encoder..... | 6 |
+| 8.9 | Requirements for decoder..... | 6 |
+| 9 | Security considerations..... | 6 |
+| Appendix I | – Example use cases of real-time interactive multimedia service ..... | 7 |
+| I.1 | Real-time interactive multimedia service in highly rural areas..... | 7 |
+| I.2 | Real-time interactive multimedia service in maritime communication ..... | 7 |
+| I.3 | Real-time interactive multimedia service in disaster relief ..... | 8 |
+| I.4 | Real-time interactive multimedia service for managing critical events
safety..... | 9 |
+| I.5 | Real-time interactive multimedia service in emergency rescue ..... | 9 |
+| I.6 | Real-time interactive multimedia service in remote technical support ..... | 10 |
+| | Bibliography..... | 11 |
+
+
+
+# Recommendation ITU-T F.746.12
+
+# Requirements for a real-time interactive multimedia service under poor network conditions
+
+## 1 Scope
+
+This Recommendation specifies requirements for the framework to provide real-time interactive multimedia service (RIMS) under poor network conditions, and corresponding application scenarios.
+
+## 2 References
+
+The following ITU-T Recommendations and other references contain provisions which, through reference in this text, constitute provisions of this Recommendation. At the time of publication, the editions indicated were valid. All Recommendations and other references are subject to revision; users of this Recommendation are therefore encouraged to investigate the possibility of applying the most recent edition of the Recommendations and other references listed below. A list of the currently valid ITU-T Recommendations is regularly published. The reference to a document within this Recommendation does not give it, as a stand-alone document, the status of a Recommendation.
+
+- [ITU-T X.500] Recommendation ITU-T X.500 (2019), *Information technology – Open Systems Interconnection – The Directory: Overview of concepts, models and services.*
+- [ITU-T X.511] Recommendation ITU-T X.511 (2019), *Information technology – Open Systems Interconnection – The Directory: Abstract service definition.*
+- [ITU-T Y.2201] Recommendation ITU-T Y.2201 (2009), *Requirements and capabilities for ITU-T NGN.*
+- [ITU-T Y.2701] Recommendation ITU-T Y.2701 (2007), *Security requirements for NGN release 1.*
+
+## 3 Definitions
+
+### 3.1 Terms defined elsewhere
+
+This Recommendation uses the following terms defined elsewhere:
+
+**3.1.1 application service** [b-ITU-T H.360]: A network-based service involving the transmission and/or processing of multimedia information.
+
+**3.1.2 call control** [b-ITU-T G.8081]: Call control is a signalling association between one or more user applications and the network to control the set-up, release, modification and maintenance of sets of connections.
+
+**3.1.3 directory server** [b-ITU-T X.518]: A DSA or an LDAP server.
+
+**3.1.4 decoder** [b-ITU-T H.265]: An embodiment of a decoding process.
+
+**3.1.5 encoder** [b-ITU-T H.265]: An embodiment of an encoding process.
+
+**3.1.6 multimedia service** [b-ITU-T Q.1743]: Services that handle several types of media such as audio and video in a synchronized way from the user's point of view. A multimedia service may involve multiple parties, multiple connections, and the addition or deletion of resources and users within a single communication session.
+
+### 3.2 Terms defined in this Recommendation
+
+None.
+
+## 4 Abbreviations
+
+This Recommendation uses the following abbreviations and acronyms:
+
+| | |
+|------|------------------------------------------|
+| AC | Application Client |
+| ASU | Application Service Unit |
+| CCSU | Call Control Service Unit |
+| DS | Directory Server |
+| DSA | Directory System Agent |
+| FEC | Forward Error Correction |
+| LDAP | Lightweight Directory Access Protocol |
+| MPSU | Media Processing Service Unit |
+| MSSU | Media Storage Service Unit |
+| RIMS | Real-time Interactive Multimedia Service |
+| SAN | Storage Area Networking |
+| VACU | Video and Audio Capture Unit |
+| VARU | Video and Audio Render Unit |
+| VSAT | Very Small Aperture Terminal |
+
+## 5 Convention
+
+In this Recommendation:
+
+- The phrase "is required to" indicates a requirement that must be strictly followed and from which no deviation is permitted if conformity to this Recommendation is to be claimed.
+- The phrase "is recommended" indicates a requirement that is recommended but which is not absolutely required. Thus, this requirement need not be present to claim conformity.
+- The phrase "can optionally" indicates an optional requirement that is permissible, without implying any sense of being recommended. This term is not intended to imply that the vendor's implementation must provide the option and the feature can be optionally enabled by the network operator or service provider. Rather, it means the vendor may optionally provide the feature and still claim conformity with the specification.
+
+## 6 Overview
+
+Real-time multimedia service plays an increasingly important role in many scenarios and situations with poor network conditions, e.g., emergency relief, medical emergency, remote education, emergency communication, maritime communication, remote technical support and vehicle communication [b-Martini] [b-Tsou].
+
+In most of these scenarios, the communications infrastructure is broken (in disaster scenarios) or even non-existent (in remote rural areas). Thus, the underlying network conditions are very poor. Packets often suffer a high bit error rate (burst packet loss), significant delay jitter or long transmission delay. The wireless environment changes rapidly, and the transmission power of nodes is often adjusted, which leads to frequent changes of network topology [b-Ni].
+
+There are several methods deployed, such as flexible macroblock ordering [b-ITU-T H.264], slice segment and key frames re-synchronization, to provide resilient multimedia services over the Internet. However, under poor network conditions, the transmission issues previously mentioned cannot be solved by these methods [b-Wang] [b-Zhang].
+
+Forward error correction (FEC) performs well with random error, but cannot deal with burst errors. In the situations previously mentioned, encoding every packet with FEC will overburden the network. An automatic repeat request sends data repeatedly when the network condition goes badly and makes congestion worse. When some links are instable or with high latency (> 200 ms), e.g., satellite links, the general signalling control mechanism, such as that specified in [b-ITU-T H.323], may lead to frequent re-connection.
+
+To overcome these issues, many vendors have proposed proprietary solutions to provide better performance, which leads to the problem of interoperability [b-Nguyen]. This Recommendation focuses on the requirements of RIMS under poor network conditions.
+
+## 7 Key components of a real-time interactive multimedia service system
+
+This clause presents a reference framework for a RIMS system, which is shown in Figure 7-1. It consists of an application service unit (ASU), application client (AC), call control service unit (CCSU), media processing service unit (MPSU), media storage service unit (MSSU), directory server (DS), encoder, decoder, video and audio capture unit (VACU) and a video and audio render unit (VARU).
+
+Unless explicitly stated in the text, the framework depicted in the figures and functions in this Recommendation are logical and thus do not necessarily represent a particular physical implementation.
+
+The ASU, CCSU, MPSU, MSSU and DS are deployed in a RIMS service node. The ASU provides specific application service(s) to RIMS users. Its main functions include access registration, access authentication, identification, authorization, presence, business processing, information management and target media serving function selection. The CCSU is a signalling association unit between service node equipment and user equipment to control the set-up, release, modification and maintenance of sets of connections. The MPSU provides video and audio processing services. Its main functions include media reception, media mixing, media transcoding, media routing, media transmission, media forwarding and media replication. The MSSU is used to retrieve, store media and provide media serving capability. Its main functions include media storage, media serving, media indexing and media downloading. The DS is an entity that stores information about objects as records and provides records to other units. It can return directory information when receiving a request over the directory access protocol or lightweight directory access protocol (LDAP).
+
+RIMS user equipment consists of five units: AC; encoder; decoder; VACU; and VARU. The AC is an agent that initiates requests and receives ASU responses. The encoder is an embodiment of an encoding process. The decoder is an embodiment of a decoding process. The VACU captures video and audio media streams, such as a camera or microphone. The VARU feeds media streams to devices, such as a screen or loudspeaker.
+
+
+
+The diagram illustrates the reference framework for a real-time interactive multimedia service system. It is divided into two main components: RIMS user equipment and RIMS service node equipment.
+
+**RIMS user equipment (Yellow Box):**
+
+- Application client
+- Video and audio capture unit
+- Encoder
+- Decoder
+- Video and audio render unit
+
+**RIMS service node equipment (Green Box):**
+
+- Application service unit
+- Call control service unit
+- Media processing service unit
+- Media storage service unit
+- Directory server
+
+**Interactions:**
+
+- User commands: From Application client to Application service unit.
+- Call control signalling: Bidirectional between Application client and Call control service unit.
+- Encoded media packets: From Encoder to Media processing service unit, and from Media processing service unit to Decoder.
+- Directory packets (dashed lines): Between Application service unit and Directory server, and between Media storage service unit and Directory server.
+
+**Legend:**
+
+- Signalling packet: Thin solid line
+- Media packet: Thick solid line
+- Directory packet: Dashed line
+- User equipment: Yellow box
+- Service node equipment: Green box
+
+F.746.12(22)
+
+Figure 7-1: Reference framework for real-time interactive multimedia service system. The diagram shows the interaction between RIMS user equipment and RIMS service node equipment. RIMS user equipment (yellow box) contains an Application client, Video and audio capture unit, Encoder, Decoder, and Video and audio render unit. RIMS service node equipment (green box) contains an Application service unit, Call control service unit, Media processing service unit, Media storage service unit, and Directory server. Arrows indicate the flow of User commands, Call control signalling, and Encoded media packets. A legend at the bottom defines the packet types and equipment types.
+
+**Figure 7-1 – Reference framework for real-time interactive multimedia service system**
+
+# 8 Requirements for real-time interactive multimedia service system
+
+This clause presents the requirements for a RIMS system.
+
+### 8.1 General requirements
+
+GEN-01: The system is required to configure routing policies between different service nodes directly, based on emergency communication requirements, to realize fast-forwarding of signalling and media packets.
+
+GEN-02: The system is required to provide mechanisms for adjusting video coding parameters, including video resolution, frame rate, bit rate and network abstract layer (NAL) size.
+
+GEN-03: The system is required to provide mechanisms for adjusting audio coding parameters including audio sampling frequency, sample accuracy, bit rate and sound channel numbers.
+
+GEN-04: The system can optionally provide protecting mechanisms for important information including video sequence head, image frame head, strip head, motion vector information and I-frame.
+
+GEN-05: The system is required to set maximal priority of audio communication under low-speed network conditions.
+
+GEN-06: The system can optionally deliver media packets using the network multicast protocol.
+
+GEN-07: The system is required to ensure that high-priority uses have priority of service over low-priority uses.
+
+### 8.2 Requirements for application service unit
+
+ASU-01: ASU is required to support the authentication of users and devices.
+
+ASU-02: ASU is required to support the authorization of allowed uses.
+
+ASU-03: ASU is required to respond to AC operation requests and convert them into commands for other functional units.
+
+ASU-04: ASU is required to provide business processing functions including video calling, video conferencing and video surveillance.
+
+ASU-05: ASU is required to collect information about system status including user device online status and session status.
+
+### **8.3 Requirements for application client**
+
+AC-01: AC is required to provide services configuration function.
+
+AC-02: AC is required to provide system status display function.
+
+AC-03: AC is required to provide system configuration function.
+
+AC-04: AC is recommended to provide shortcuts for control services.
+
+### **8.4 Requirements for call control service unit**
+
+CCSU-01: CCSU is required to negotiate the media parameters for the two parties during a session establishment stage.
+
+CCSU-02: CCSU is recommended to ensure effective connection of signalling in a network environment with long time delay and frequent interruptions.
+
+CCSU-03: CCSU is required to control the creation or closure of media transfer channels.
+
+CCSU-04: CCSU is recommended to update I-frame using a signalling protocol to speed up the synchronization of I-frames.
+
+CCSU-05: CCSU can optionally configure the interval of I-frames using a signalling protocol.
+
+### **8.5 Requirements for media processing service unit**
+
+MPSU-01: MPSU is required to provide media delivery.
+
+MPSU-02: MPSU is required to provide video compositing.
+
+MPSU-03: MPSU is required to provide audio mixing.
+
+MPSU-04: MPSU is required to provide media transcoding.
+
+MPSU-05: MPSU is recommended to support constant bit rate flow control to avoid bursts-induced traffic congestion.
+
+MPSU-06: MPSU can optionally smooth traffic through setting cache size, I-frame interval, I-frame size and key message retransmission frequency.
+
+MPSU-07: MPSU is required to unify the transport packaging format and related parameters including package length and timestamp.
+
+### **8.6 Requirements for media storage service unit**
+
+MSSU-01: MSSU is required to support media storage and streaming.
+
+MSSU-02: MSSU can optionally receive media packets through network storage facilities including storage area networking and network attached storage.
+
+### **8.7 Requirements for directory server**
+
+DS-01: DS is required to support storage and synchronization of static information.
+
+DS-02: DS is required to synchronize static information with an ASU.
+
+DS-03: Each request may be accompanied by information in support of security mechanisms for protecting directory information. These definitions are contained in [ITU-T X.500].
+
+DS-04: The DS is required to support interrogation, retrieval and modification of directory information. This service is specified in [ITU-T X.511].
+
+### **8.8 Requirements for encoder**
+
+En-01: Encoder is required to implement media coding according to the strategy that carries out coding adjustment with respect to the network state feedback information.
+
+En-02: Encoder is recommended to provide type identifiers for its underlying channels (e.g., fixed network, satellite network and mobile network) in the registration message.
+
+En-03: Encoder is recommended to contain the description of coding capability in the registration message to improve negotiating efficiency.
+
+En-04: Encoder is recommended to support constant bit rate flow control to bursts-induced traffic congestion.
+
+En-05: Encoder can optionally assist in managing sending traffic load through setting cache size, I-frame interval, I-frame size, key message retransmission frequency, etc.
+
+En-06: Encoder is required to unify the transport packaging format and related parameters including package length and timestamp.
+
+### **8.9 Requirements for decoder**
+
+De-01: Decoder is required to implement media decoding according to the strategy.
+
+De-02: Decoder is required to support adaptive decoding function, within the capacity range of media negotiation, to automatically adapt to media flow.
+
+De-03: Decoder can optionally provide adjusting mechanisms of buffer threshold to adapt and eliminate out-of-order packets, duplication and jitter in network transmission, and to ensure the synchronization of video and audio media.
+
+## **9 Security considerations**
+
+It is recommended that the security requirements of [ITU-T Y.2201], [ITU-T Y.2701], and applicable ITU-T X, ITU-T Y and ITU-T M series security Recommendations be taken into consideration, including access control, authentication, data confidentiality, communications security, data integrity, availability and privacy.
+
+## Appendix I
+
+## Example use cases of real-time interactive multimedia service
+
+(This appendix does not form an integral part of this Recommendation.)
+
+### I.1 Real-time interactive multimedia service in highly rural areas
+
+Figure I.1 shows that, given their poor communication infrastructures, satellites can provide worldwide Internet access for some highly rural areas. However, the long latency associated with satellite channels ( $> 200$ ms) often triggers session timeout. RIMSs, such as education and medical diagnosis delivered remotely, are expected to be tolerant of long latency. This is one RIMS scenario.
+
+
+
+The diagram illustrates a network architecture for real-time interactive multimedia services in rural areas. At the top center is a 'Satellite'. It has wireless links (yellow lightning bolts) to a 'Satellite master station' and a 'VSAT'. The 'Satellite master station' is connected via 'Cable' to a 'Fixed network' cloud. This cloud connects to a 'RIMS user' and a 'RIMS service node' (containing four server icons) via 'Fixed network' lines. The 'VSAT' is connected via 'Cable' to a 'Communication station' tower. This tower has a wireless link to a 'RIMS user' and another wireless link to a 'Communication vehicle' (a truck). The 'Communication vehicle' further connects wirelessly to another 'RIMS user'. All rural 'RIMS user' icons are enclosed in dashed boxes. The bottom right area is labeled 'Rural areas' and includes the code 'F.746.12(22)'.
+
+Diagram of real-time interactive multimedia service in highly rural areas
+
+**Figure I.1 – Real-time interactive multimedia service in highly rural areas**
+
+### I.2 Real-time interactive multimedia service in maritime communication
+
+Figure I.2 shows that, during an ocean voyage, uses on ships mainly rely on satellite and other wireless means to communicate with remote users in real-time multimedia. In this scenario, the channel state, such as end-to-end delay and the available bandwidth, changes dynamically. RIMS system can adapt to the coding strategy of the sender (e.g., resolution, frame rate, code rate and NAL size) and the flow shaping strategy (e.g., I-frame interval and cache setting) according to the changing status of the channel.
+
+
+
+Diagram of real-time interactive multimedia service in maritime communication. A RIMS user on land is connected via a fixed network to a cloud labeled 'Fixed network'. This cloud is connected to another 'Fixed network' cloud, which in turn connects to a 'RIMS service node' (four server icons). The second 'Fixed network' cloud is also connected to a 'Satellite master station' (ground station). The 'Satellite master station' has a bidirectional link to a 'Satellite' in space. The 'Satellite' has a bidirectional link to a ship at sea. The ship is connected to another 'RIMS user' on board. The diagram is labeled F.746.12(22).
+
+**Figure I.2 – Real-time interactive multimedia service in maritime communication**
+
+### I.3 Real-time interactive multimedia service in disaster relief
+
+RIMS during disaster relief operations is crucial. In this scenario, the communication infrastructure is broken. As shown in Figure I.3, temporary *ad hoc* networks are set up to provide local network connections, and satellite networks can provide remote connections. The RIMS system, which is on top of these networks, can provide interactive multimedia services for disaster medicine and disaster management. However, the quality of wireless links is poor and varies rapidly. The network topology is also unstable. The service is expected to perform at its best in these hostile conditions with limited resources.
+
+
+
+Diagram of real-time interactive multimedia service in disaster relief. A RIMS user on land is connected via a fixed network to a 'Satellite master station' (ground station). The 'Satellite master station' has a bidirectional link to a 'Satellite' in space. The 'Satellite' has a bidirectional link to a 'Local network' (dashed box). Inside the 'Local network', there are 'On-board equipment' (a car), 'Unmanned aerial vehicles' (a drone), a 'Helicopter', and three 'User' icons. All these components are interconnected by red dashed double-headed arrows, forming a mesh network. The diagram is labeled F.746.12(22).
+
+**Figure I.3 – Real-time interactive multimedia service in disaster relief**
+
+### I.4 Real-time interactive multimedia service for managing critical events safety
+
+A large number of terminals need to access the network in some major events, such as celebrations, conferences and exhibitions. Traffic demands can easily overwhelm the capacities of mobile networks. Figure I.4 shows that the RIMS system can be deployed to provide real-time monitoring and management of critical parts of these activities.
+
+
+
+This diagram illustrates a real-time interactive multimedia service for managing critical events safety. It features a central 'Headquarters' unit, represented by a small inset image of a control room, connected by red dashed lines to four 'RIMS user' units. Each 'RIMS user' is depicted with a person icon. The background is an aerial view of a large stadium or arena with surrounding infrastructure, showing the deployment of the system for event management. The text 'F.746.12(22)' is visible in the bottom right corner.
+
+Diagram of RIMS system for managing critical events safety.
+
+Figure I.4 – Real-time interactive multimedia service for managing critical events safety
+
+### I.5 Real-time interactive multimedia service in emergency rescue
+
+Visual command and remote diagnostics are often needed for emergency rescue in underground situations such as mass transit railways, garages and tunnels. Figure I.5 shows the application of a RIMS system to an underground railway scenario.
+
+
+
+This diagram shows the application of a RIMS system in an underground railway scenario. A 'Headquarters' unit, shown in an inset, is connected by blue dashed lines to three 'RIMS user' units. The 'RIMS user' units are positioned at different levels of the railway: one on the surface, one on an escalator, and one inside a tunnel. Each 'RIMS user' is represented by a person icon. The background depicts a 3D model of a subway station and tunnel with trains, illustrating the system's use in emergency rescue operations. The text 'F.746.12(22)' is visible in the bottom right corner.
+
+Diagram of RIMS system in an underground railway scenario.
+
+Figure I.5 – Real-time interactive multimedia service in emergency rescue
+
+### I.6 Real-time interactive multimedia service in remote technical support
+
+To conduct tasks in highly dangerous situations, such as offshore platform operation, high-voltage cable inspection and fire-fighting operation, high-definition image backhaul and communication provided by RIMS system in real time are critical for technical support. Figure I.6 shows this scenario.
+
+
+
+RIMS user
+
+Headquarters
+
+F.746.12(22)
+
+Diagram illustrating the RIMS system for remote technical support. A worker on an offshore platform (RIMS user) is shown in a circular inset, with an orange arrow pointing from the worker to a satellite in space. Another orange arrow points from the satellite to a person at a computer workstation (Headquarters). The background shows an offshore oil rig and a cloudy sky.
+
+**Figure I.6 – Real-time interactive multimedia service in remote technical support**
+
+## Bibliography
+
+- [b-ITU-T G.8081] Recommendation ITU-T G.8081/Y.1353 (2012), *Terms and definitions for automatically switched optical networks*.
+- [b-ITU-T H.264] Recommendation ITU-T H.264 (2021), *Advanced video coding for generic audiovisual services*.
+- [b-ITU-T H.265] Recommendation ITU-T H.265 (2021), *High efficiency video coding*.
+- [b-ITU-T H.323] Recommendation ITU-T H.323 (2022), *Packet-based multimedia communications systems*.
+- [b-ITU-T H.360] Recommendation ITU-T H.360 (2004), *An architecture for end-to-end QoS control and signalling*.
+- [b-ITU-T Q.1743] Recommendation ITU-T Q.1743 (2016), *IMT-Advanced references to Release 11 of LTE-Advanced evolved packet core network*.
+- [b-ITU-T X.518] Recommendation ITU-T X.518 (2019), *Information technology – Open Systems Interconnection – The Directory: Procedures for distributed operation*.
+- [b-Martini] Martini, M.G., Iacobelli, L., Bergeron, C., Hewage, C.T., Panza, G., Piri, E., Vehkapera, J., Amon, P., Mazzotti, M., Savino, K., Bokor, L. (2015). Real-time multimedia communications in medical emergency-the CONCERTO project solution. In: *Proc. 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society*, pp. 7324-7. doi: 10.1109/EMBC.2015.7320083
+- [b-Nguyen] Nguyen, T., Yegenoglu, F., Sciuto, A. Subbarayan, R. (2001). Voice over IP service and performance in satellite networks. *IEEE Commun. Mag.* **39**(3), pp. 164-171. doi: 10.1109/35.910604
+- [b-Ni] Ni, Q., Li, T., Turletti, T., Xiao, Y. (2005). Saturation throughput analysis of error-prone 802.11 wireless networks. *Wireless Commun. Mobile Comput.* **5**(8), pp. 945-956.
+- [b-Tsou] Tsou, M.H., Jung, C.T., Allen, C., Yang, J.A., Han, S.Y., Spitzberg, B.H., Dozier, J. (2017). Building a real-time geo-targeted event observation (geo) viewer for disaster management and situation awareness. In: Peterson, M. (eds). *Advances in Cartography and GIScience. ICACI 2017. Lecture Notes in Geoinformation and Cartography*. Berlin: Springer Nature. doi: 10.1007/978-3-319-57336-6\_7
+- [b-Wang] Wang, Y., Jing, X., Tham, J.Y., Goh, K.H., Lee, W.S. (2013). Error-resilient packet reordering for compressed video transmission over error-prone networks. In: *Proc. 7th International Conference on Ubiquitous Information Management and Communication (ICUIMC '13)*, Article 28, 1–6. New York, NY: Association for Computing Machinery. doi: 10.1145/2448556.2448584
+- [b-Zhang] Zhang, Y., Gao, W., Lu, Y., Huang, Q., Zhao, D. (2007). Joint source-channel rate-distortion optimization for H. 264 video coding over error-prone networks. *IEEE Trans. Multimedia* **9**(3), pp. 445-454. doi: 10.1109/TMM.2006.887989.
+
+
+
+
+
+## SERIES OF ITU-T RECOMMENDATIONS
+
+| | |
+|-----------------|-----------------------------------------------------------------------------------------------------------------------------------------------------------|
+| Series A | Organization of the work of ITU-T |
+| Series D | Tariff and accounting principles and international telecommunication/ICT economic and policy issues |
+| Series E | Overall network operation, telephone service, service operation and human factors |
+| Series F | Non-telephone telecommunication services |
+| Series G | Transmission systems and media, digital systems and networks |
+| Series H | Audiovisual and multimedia systems |
+| Series I | Integrated services digital network |
+| Series J | Cable networks and transmission of television, sound programme and other multimedia signals |
+| Series K | Protection against interference |
+| Series L | Environment and ICTs, climate change, e-waste, energy efficiency; construction, installation and protection of cables and other elements of outside plant |
+| Series M | Telecommunication management, including TMN and network maintenance |
+| Series N | Maintenance: international sound programme and television transmission circuits |
+| Series O | Specifications of measuring equipment |
+| Series P | Telephone transmission quality, telephone installations, local line networks |
+| Series Q | Switching and signalling, and associated measurements and tests |
+| Series R | Telegraph transmission |
+| Series S | Telegraph services terminal equipment |
+| Series T | Terminals for telematic services |
+| Series U | Telegraph switching |
+| Series V | Data communication over the telephone network |
+| Series X | Data networks, open system communications and security |
+| Series Y | Global information infrastructure, Internet protocol aspects, next-generation networks, Internet of Things and smart cities |
+| Series Z | Languages and general software aspects for telecommunication systems |
\ No newline at end of file
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+
+
+# Recommendation **ITU-T F.746.16 (12/2022)**
+
+SERIES F: Non-telephone telecommunication services
+Multimedia services
+
+---
+
+## **Technical requirements and evaluation methods of intelligence levels of intelligent customer service systems**
+
+
+
+The logo of the International Telecommunication Union (ITU) is located in the bottom right corner. It features a blue circular emblem with a stylized globe and the letters 'ITU' in white.
+
+ITU logo
+
+## ITU-T F-SERIES RECOMMENDATIONS **NON-TELEPHONE TELECOMMUNICATION SERVICES**
+
+### **TELEGRAPH SERVICE**
+
+| | |
+|-----------------------------------------------------------------|-------------|
+| Operating methods for the international public telegram service | F.1–F.19 |
+| The gentex network | F.20–F.29 |
+| Message switching | F.30–F.39 |
+| The international telemessages service | F.40–F.58 |
+| The international telex service | F.59–F.89 |
+| Statistics and publications on international telegraph services | F.90–F.99 |
+| Scheduled and leased communication services | F.100–F.104 |
+| Phototelegraph service | F.105–F.109 |
+
+### **MOBILE SERVICE**
+
+| | |
+|--------------------------------------------------------|-------------|
+| Mobile services and multdestination satellite services | F.110–F.159 |
+|--------------------------------------------------------|-------------|
+
+### **TELEMATIC SERVICES**
+
+| | |
+|-------------------------------------------|-------------|
+| Public facsimile service | F.160–F.199 |
+| Teletex service | F.200–F.299 |
+| Videotex service | F.300–F.349 |
+| General provisions for telematic services | F.350–F.399 |
+
+### **MESSAGE HANDLING SERVICES**
+
+| | |
+|---------------------------|-------------|
+| MESSAGE HANDLING SERVICES | F.400–F.499 |
+|---------------------------|-------------|
+
+### **DIRECTORY SERVICES**
+
+| | |
+|--------------------|-------------|
+| DIRECTORY SERVICES | F.500–F.549 |
+|--------------------|-------------|
+
+### **DOCUMENT COMMUNICATION**
+
+| | |
+|--------------------------------------|-------------|
+| Document communication | F.550–F.579 |
+| Programming communication interfaces | F.580–F.599 |
+
+### **DATA TRANSMISSION SERVICES**
+
+| | |
+|----------------------------|-------------|
+| DATA TRANSMISSION SERVICES | F.600–F.699 |
+|----------------------------|-------------|
+
+### **MULTIMEDIA SERVICES**
+
+| | |
+|----------------------------|--------------------|
+| MULTIMEDIA SERVICES | F.700–F.799 |
+|----------------------------|--------------------|
+
+### **ISDN SERVICES**
+
+| | |
+|---------------|-------------|
+| ISDN SERVICES | F.800–F.849 |
+|---------------|-------------|
+
+### **UNIVERSAL PERSONAL TELECOMMUNICATION**
+
+| | |
+|--------------------------------------|-------------|
+| UNIVERSAL PERSONAL TELECOMMUNICATION | F.850–F.899 |
+|--------------------------------------|-------------|
+
+### **ACCESSIBILITY AND HUMAN FACTORS**
+
+| | |
+|---------------------------------|-------------|
+| ACCESSIBILITY AND HUMAN FACTORS | F.900–F.999 |
+|---------------------------------|-------------|
+
+*For further details, please refer to the list of ITU-T Recommendations.*
+
+# Recommendation ITU-T F.746.16
+
+# Technical requirements and evaluation methods of intelligence levels of intelligent customer service systems
+
+## Summary
+
+The intelligent customer service system (ICSS) can provide more convenient, efficient, and stable services for users through the application of artificial intelligence (AI) technologies such as speech recognition, text to speech and natural language processing. There is value therefore in improving and evaluating the intelligence levels of the intelligent customer service system. Recommendation ITU-T F.746.16 specifies the requirements and methods for evaluating the system intelligence of intelligent customer service systems through four aspects which are; the basic functions, the core technologies of AI, the system maturation and the service experience.
+
+## History
+
+| Edition | Recommendation | Approval | Study Group | Unique ID* |
+|---------|----------------|------------|-------------|---------------------------------------------------------------------------|
+| 1.0 | ITU-T F.746.16 | 2022-12-14 | 16 | 11.1002/1000/15190 |
+
+## Keywords
+
+Intelligent customer service, intelligence levels.
+
+---
+
+\* To access the Recommendation, type the URL in the address field of your web browser, followed by the Recommendation's unique ID. For example, .
+
+## FOREWORD
+
+The International Telecommunication Union (ITU) is the United Nations specialized agency in the field of telecommunications, information and communication technologies (ICTs). The ITU Telecommunication Standardization Sector (ITU-T) is a permanent organ of ITU. ITU-T is responsible for studying technical, operating and tariff questions and issuing Recommendations on them with a view to standardizing telecommunications on a worldwide basis.
+
+The World Telecommunication Standardization Assembly (WTSA), which meets every four years, establishes the topics for study by the ITU-T study groups which, in turn, produce Recommendations on these topics.
+
+The approval of ITU-T Recommendations is covered by the procedure laid down in WTSA Resolution 1.
+
+In some areas of information technology which fall within ITU-T's purview, the necessary standards are prepared on a collaborative basis with ISO and IEC.
+
+## NOTE
+
+In this Recommendation, the expression "Administration" is used for conciseness to indicate both a telecommunication administration and a recognized operating agency.
+
+Compliance with this Recommendation is voluntary. However, the Recommendation may contain certain mandatory provisions (to ensure, e.g., interoperability or applicability) and compliance with the Recommendation is achieved when all of these mandatory provisions are met. The words "shall" or some other obligatory language such as "must" and the negative equivalents are used to express requirements. The use of such words does not suggest that compliance with the Recommendation is required of any party.
+
+## INTELLECTUAL PROPERTY RIGHTS
+
+ITU draws attention to the possibility that the practice or implementation of this Recommendation may involve the use of a claimed Intellectual Property Right. ITU takes no position concerning the evidence, validity or applicability of claimed Intellectual Property Rights, whether asserted by ITU members or others outside of the Recommendation development process.
+
+As of the date of approval of this Recommendation, ITU had not received notice of intellectual property, protected by patents/software copyrights, which may be required to implement this Recommendation. However, implementers are cautioned that this may not represent the latest information and are therefore strongly urged to consult the appropriate ITU-T databases available via the ITU-T website at .
+
+© ITU 2023
+
+All rights reserved. No part of this publication may be reproduced, by any means whatsoever, without the prior written permission of ITU.
+
+## Table of Contents
+
+###### Page
+
+| | | |
+|------|-------------------------------------------------------------|----|
+| 1 | Scope ..... | 1 |
+| 2 | References..... | 1 |
+| 3 | Definitions ..... | 1 |
+| 3.1 | Terms defined elsewhere ..... | 1 |
+| 3.2 | Terms defined in this Recommendation..... | 1 |
+| 4 | Abbreviations and acronyms ..... | 2 |
+| 5 | Conventions ..... | 2 |
+| 6 | Architecture overview ..... | 2 |
+| 7 | Intelligence levels of ICSS ..... | 4 |
+| 8 | Basic functions of ICSS..... | 4 |
+| 8.1 | Multi-channel management ..... | 5 |
+| 8.2 | Multi-media message interaction ..... | 5 |
+| 8.3 | Intelligent dialogue..... | 5 |
+| 8.4 | Identity recognition ..... | 6 |
+| 8.5 | Knowledge base management ..... | 6 |
+| 8.6 | Work order management ..... | 6 |
+| 8.7 | Human-machine collaboration ..... | 7 |
+| 8.8 | Abnormal session management..... | 7 |
+| 9 | Artificial intelligence core technical ability of ICSS..... | 7 |
+| 9.1 | Speech recognition ..... | 8 |
+| 9.2 | Text to speech..... | 9 |
+| 9.3 | Single-round dialogue ..... | 9 |
+| 9.4 | Multi-round dialogue..... | 10 |
+| 9.5 | Knowledge graph..... | 11 |
+| 9.6 | Multilingual interaction ..... | 11 |
+| 9.7 | Optical character recognition ..... | 11 |
+| 9.8 | Picture content recommendation ..... | 11 |
+| 10 | ICSS system maturity ..... | 12 |
+| 10.1 | Data visibility ..... | 12 |
+| 10.2 | Usability ..... | 12 |
+| 10.3 | Reliability ..... | 13 |
+| 10.4 | Security..... | 13 |
+| 10.5 | Maintainability ..... | 13 |
+| 10.6 | Auditability..... | 14 |
+| 11 | Service experience of enterprises ..... | 14 |
+| 11.1 | Data access ability ..... | 15 |
+| 11.2 | Human intervention ability..... | 15 |
+
+| | Page |
+|-------------------------------------------|-------------|
+| 11.3 Emotional pacification ability ..... | 15 |
+| 11.4 Assistant service ability ..... | 15 |
+| 11.5 Customer satisfaction ..... | 16 |
+
+# **Technical requirements and evaluation methods of intelligence levels of intelligent customer service systems**
+
+# **1 Scope**
+
+This Recommendation aims to establish an indicator system to evaluate the intelligence levels of intelligent customer service systems (ICSS) for human-machine interactions. The intelligent customer service system mentioned in this Recommendation includes a variety of product forms such as outbound service robots, inbound service robots, and text service robots.
+
+This Recommendation considers four main aspects:
+
+- The basic functions of ICSS;
+- The artificial intelligence core technical abilities of ICSS;
+- The system maturation of ICSS;
+- The service experience of enterprises.
+
+## **2 References**
+
+The following ITU-T Recommendations and other references contain provisions which, through reference in this text, constitute provisions of this Recommendation. At the time of publication, the editions indicated were valid. All Recommendations and other references are subject to revision; users of this Recommendation are therefore encouraged to investigate the possibility of applying the most recent edition of the Recommendations and other references listed below. A list of the currently valid ITU-T Recommendations is regularly published. The reference to a document within this Recommendation does not give it, as a stand-alone document, the status of a Recommendation.
+
+None.
+
+# **3 Definitions**
+
+### **3.1 Terms defined elsewhere**
+
+None.
+
+### **3.2 Terms defined in this Recommendation**
+
+This Recommendation defines the following terms:
+
+**3.2.1 intelligent customer service system:** A customer service system based on natural language processing, speech recognition, text to speech and other artificial intelligence technologies. After converging the user's questions through single or multiple rounds of conversation, the intelligent customer service system relies on a maintained background knowledge base and interface components to realize intelligent dialogue.
+
+**3.2.2 single-round dialogue:** A conversation between a human and an intelligent customer service system.
+
+**3.2.3 multi-round dialogue:** More than one conversation between a human and an intelligent customer service system in the process for solving complex problems.
+
+# 4 Abbreviations and acronyms
+
+This Recommendation uses the following abbreviations and acronyms:
+
+| | |
+|------|-------------------------------------|
+| APP | Application |
+| BLEU | Bilingual Evaluation Understudy |
+| CRM | Customer Relationship Management |
+| ICSS | Intelligent Customer Service System |
+| KM | Knowledge Management |
+| MOS | Mean Opinion Score |
+| NLG | Natural Language Generation |
+| NLP | Natural Language Processing |
+| NLU | Natural Language Understanding |
+| OCR | Optical Character Recognition |
+| PII | Personally Identifiable Information |
+| SER | Sentence Error Rate |
+| TTS | Text to Speech |
+| WER | Word Error Rate |
+
+## 5 Conventions
+
+In this Recommendation:
+
+- The keywords "**is required to**" indicate a requirement which must be strictly followed and from which no deviation is permitted if conformance to this document is to be claimed.
+- The keywords "**is recommended**" indicate a requirement which is recommended but which is not absolutely required. Thus, this requirement needs not be present to claim conformance.
+- The keywords "**can optionally**" and "**may**" indicate an optional requirement which is permissible, without implying any sense of being recommended. These terms are not intended to imply that the vendor's implementation must provide the option and the feature can be optionally enabled by the network operator/service provider. Rather, it means the vendor may optionally provide the feature and still claim conformance with the specification.
+
+# 6 Architecture overview
+
+Figure 1 shows the functional structure of the intelligent customer service system.
+
+
+
+```
+
+graph TD
+ A[Customers access through multiple channels] --> B[Identification module]
+ B --> C[Central control module]
+ C --> D[Intelligent dialogue management]
+ C --> E[Manual customer service]
+ D --> F[Work order management]
+ E --> F
+ F --> G[CRM system]
+ F --> H[KM system]
+ D --- D1[NLP]
+ D --- D2[NLU]
+ D --- D3[NLG]
+ D --- D4[TTS]
+ D --- D5[Knowledge base]
+ D1 & D2 & D3 & D4 & D5 --> E
+ D1 & D2 & D3 & D4 & D5 --> F
+ G <--> F
+ H <--> F
+ I[System functions analysis] -.-> C
+ I -.-> D
+ I -.-> E
+ I -.-> F
+ J[F.746.16(22)]
+
+```
+
+Flowchart of the Functions structure of ICSS. The flow starts with 'Customers access through multiple channels' at the top, followed by 'Identification module', 'Central control module', and 'Intelligent dialogue management'. The 'Intelligent dialogue management' module contains sub-components: NLP, NLU, NLG, TTS, and Knowledge base. It connects to 'Manual customer service' and 'Work order management'. 'Work order management' connects to 'CRM system' and 'KM system'. A vertical bar on the right labeled 'System functions analysis' spans from the 'Central control module' down to the 'Work order management' level. The reference code F.746.16(22) is at the bottom right.
+
+**Figure 1 – Functions structure of ICSS**
+
+**Customers access through multiple channels:** This module provides users with web pages, apps, phones and other channels to access the ICSS and obtain relevant services.
+
+**Identification module:** This module of the ICSS mainly recognizes the user's speech and transforms it into text content for subsequent analysis.
+
+**Central control module:** This module further process the user's message and converts it into input content that can be recognized and understood by AI, and determines whether the message is answered by the intelligent customer service system or by a manual customer service.
+
+**Intelligent dialogue management:** This module is to understand the user's intention, match the relevant answers in the corpus, and feed back to the user through text or speech. It mainly involves natural language processing (NLP), natural language understanding (NLU), natural language generation (NLG) and other AI technologies.
+
+**Manual customer service:** Manual customer service is an important part of the ICSS, which is responsible for dealing with problems that are difficult to solve automatically by the system.
+
+**Work order management:** When the system encounters problems that are difficult to solve, the content of human-machine conversation will be saved in the form of work orders, and finally the centralized manual processing will be carried out.
+
+**CRM system and KM systems:** Customer relationship management (CRM) and knowledge management (KM) are auxiliary systems of the ICSS, which can help the ICSS better manage customer relations and business knowledge. CRM system refers to an information system for enterprises to collect, manage, analyse and use customer information by using software, hardware and network technology. KM system is an information system that collects, processes and shares all the knowledge of an organization.
+
+# 7 Intelligence levels of ICSS
+
+According to the application maturity of involved intelligent technologies, the intelligence ability of ICSS is divided into five levels. The definition and description of each level are shown in Table 1.
+
+**Table 1 – Intelligence levels for ICSS**
+
+| Intelligence levels | Definition | Description |
+|---------------------|--------------------------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+| Level-1 | No intelligence | The system only has simple basic functions and system maturity, the user experience is not satisfactory. |
+| Level-2 | Partial intelligence | Based on some basic functions and system maturity, the system has simple AI core technical capabilities, but its performance and service experience are mediocre, and users can barely accept the system. |
+| Level-3 | Conditional intelligence | The system has many basic functions, and the system supports a variety of AI core technical capabilities, and its performance is good. The service capability and system maturity of the enterprise are basically acceptable to users. |
+| Level-4 | High intelligence | The system has rich basic functions, and the system supports a variety of AI core technical capabilities, and its performance is excellent. The service ability and system maturity of the enterprise are strong, and the user acceptance is strong. |
+| Level-5 | Full intelligence | In addition to the basic functions, the system also has other extended functions, the system supports a variety of AI core technical capabilities, and its performance is excellent. The service capability and system maturity are completely acceptable to users. |
+
+## 8 Basic functions of ICSS
+
+Basic functions include multi-channel management, multimedia message interaction, intelligent recommendation, identity recognition, knowledge base management, work order management, human-machine collaboration, and session abnormal management. The intelligence level description of this dimension can be seen in Table 2.
+
+**Table 2 – Intelligence levels for basic function of ICSS**
+
+| Intelligence levels | Description |
+|---------------------|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+| Level-1 | 1) Supports at least one way to access channel.
2) Supports at least one multimedia message type. |
+| Level-2 | New relatives to the previous level:
1) Supports at least two ways to access channel.
2) Supports at least two types of multimedia messages.
3) Supports at least one way to identify the identity. |
+| Level-3 | New relatives to the previous level:
1) Supports at least three ways to access channel.
2) Supports at least three types of multimedia messages.
3) Supports the intelligent dialogue function, and predict the user's intention according to the user's behaviour track and historical question information. |
+
+**Table 2 – Intelligence levels for basic function of ICSS**
+
+| Intelligence levels | Description |
+|---------------------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+| | 4) Supports at least two ways to identify the identity.
5) Supports knowledge base management. |
+| Level-4 | New relatives to the previous level:
1) Supports at least four ways to access channel.
2) Supports at least four types of multimedia messages.
3) Supports intelligent dialogue, and can automatically complete, prompt or correct the entered content in the process of user entering questions.
4) Supports at least three ways to identify the identity.
5) Supports common operations such as adding, deleting, modifying, and querying the knowledge base.
6) Supports work order management functions, including rapid creation of work orders, flexible configuration of work orders, one click to work orders, work order prioritization, and work order status tracking.
7) Supports intelligent customer service such as responding quickly and transferring to manual customer service in time. |
+| Level-5 | New relatives to the previous level:
1) Supports work order management functions other than the above functions.
2) Supports intelligent customer service with human-computer cooperation function, and provide process records, problem push and other assistance for manual customer service during the interaction process.
3) Supports abnormal session management. |
+
+### 8.1 Multi-channel management
+
+ICSS is recommended to support websites, APPs, e-mails and other channels.
+
+Evaluation methods:
+
+- Determine whether the customer service product supports the above channel access.
+- Determine whether the customer service product supports access through channels other than the above channels.
+
+### 8.2 Multi-media message interaction
+
+Determine whether the interactive methods supported by intelligent customer service are abundant. Customers can use speech, text, pictures, videos, expressions, custom messages and other real-time interactions during communication with the customer service to increase the friendliness and fun.
+
+Evaluation methods:
+
+- Judge the types of messages supported by the customer service system through material review and technical means, and give corresponding scores.
+
+### 8.3 Intelligent dialogue
+
+The ICSS recommends related questions based on the user's behaviour tracking, historical consultation and other information. During the interaction process, the system automatically recommends questions related to user consultation, which usually appear in the feedback answers or interaction interface.
+
+Evaluation methods:
+
+- a) When the user enters the conversation interface, judge whether the customer service can predict user questions based on historical question records or popular questions, and provide relevant pushes.
+- b) When the users ask questions, the system will automatically analyse the content that has been entered to provide completion or relevant prompts.
+
+### **8.4 Identity recognition**
+
+This indicator is to evaluate whether the intelligent customer service supports the function of identification. Considering the personally identifiable information (PII) protection, the ICSS can optionally have the function of identifying the user's identity after obtaining the user's permission. For example, the system can use voiceprint recognition, face recognition, short message service (SMS) verification code, voice call and other technologies to determine the user's identity information.
+
+Evaluation methods:
+
+- a) Check the smart customer service product information provided by the manufacturer to determine whether the smart customer service supports the identification function.
+- b) According to the product description, the test system can correctly identify the user's identity.
+
+### **8.5 Knowledge base management**
+
+This indicator is to evaluate the richness and self-learning function of the knowledge base. The ICSS is recommended to include corpus, question database and other related databases.
+
+Evaluation methods:
+
+- a) Check the smart customer service product information provided by the manufacturer to determine whether the smart customer service supports the knowledge base management function.
+- b) Check the richness of customer service knowledge base.
+- c) Test whether the knowledge base can support self-learning and establish custom questions and answers.
+
+### **8.6 Work order management**
+
+This indicator is to evaluate whether the ICSS has the work order management function. When encountered problems cannot be solved, customer service staff is required to create work orders to support functions such as flexible work order configuration, prioritization, and work order status tracking.
+
+Evaluation methods:
+
+- a) Check the smart customer service product information provided by the manufacturer to determine whether the smart customer service supports the work order management function.
+- b) Check the operating instructions of the work order management system, whether it supports flexible configuration of work order rules, one-click transfer of work orders, provision of hierarchical services, priority sorting, and work order status tracking functions according to the customer's customer service needs.
+- c) Other functions supported by the work order management system.
+
+For example: The enterprise can set the work orders of users such as VIP and special strategy risks as priority work orders. When customer service personnel of a certain business type receive other business, they can carry out internal transfer orders. Both the internal system and users can understand the progress of the corresponding work order processing.
+
+### 8.7 Human-machine collaboration
+
+This indicator is to evaluate the ability of the intelligent customer service and the manual customer service to solve customer problems collaboratively. When encountered problems cannot be solved by the customer service system of the machine, it supports transfer to manual service. Then the human service and the customer service system will cooperate to solve the customers' problems.
+
+Evaluation methods:
+
+- Determine whether there is support for the transfer to manual services.
+- Determine whether the smart customer service supports video calls, voice calls, text chats, etc.
+
+For example: When the machine customer service is not smooth, such as unrecognizable, multiple fuzzy recognition, user dissatisfaction, etc., observe whether the machine customer service responds as always, and judge whether it is a manual combination of machine response.
+
+### 8.8 Abnormal session management
+
+Determine whether the intelligent customer service can detect abnormal conditions such as abnormal session duration and abnormal connection, and implement corresponding countermeasures.
+
+When abnormalities such as disconnection occur in the session, the ICSS is required to save the previous records, determine the cause of the abnormality, and try to reconnect. When the system contacts the user again, it is recommended to be able to continue the topic before the interruption.
+
+Evaluation methods:
+
+- Check the session duration to determine whether it is abnormal.
+- When the session is abnormal, check whether there is an attempt to reconnect.
+- After the session is reconnected, check whether the system can continue to record the breakpoint.
+
+## 9 Artificial intelligence core technical ability of ICSS
+
+This indicator contains three types of algorithms: speech processing, natural language processing (NLP), and image processing. The intelligence level description of this dimension can be seen in Table 3.
+
+**Table 3 – Intelligence levels for artificial intelligence core technical ability**
+
+| Intelligence levels | Description |
+|---------------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+| Level-1 | - Supports speech recognition, but the performance is poor, the user's experience is poor.
- Supports speech synthesis, and users reluctantly accept the naturalness of synthetic speech.
- Supports single-round dialogue, but the performance is poor, the user's experience is poor.
|
+
+**Table 3 – Intelligence levels for artificial intelligence core technical ability**
+
+| Intelligence levels | Description |
+|---------------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+| Level-2 | New relatives to the previous level:
1) Supports speech recognition, the system performance is mediocre, the user's experience is flat.
2) Supports speech synthesis, and users basically accept the naturalness of synthetic speech.
3) Supports single-round dialogue and the system performance is mediocre, the user's experience is flat.
4) Supports multiple-round dialogue, but the performance is poor, the user's experience is poor. |
+| Level-3 | New relatives to the previous level:
1) Supports speech recognition and the system performance is good.
2) Supports speech synthesis, and users can accept the naturalness of synthetic speech.
3) Supports single-round dialogue, the system performance is good.
4) Supports multiple-round dialogue and the system performance is mediocre, the user's experience is flat.
5) Supports multilingual interaction. |
+| Level-4 | New relatives to the previous level:
1) Supports speech recognition and the performance is perfect.
2) Supports speech synthesis, and users can fully accept the naturalness of synthetic speech.
3) Supports single-round dialogue and the performance is perfect.
4) Supports multiple-round dialogue and the performance is good.
5) Supports optical character recognition (OCR) and the performance is good. |
+| Level-5 | New relatives to the previous level:
1) Supports multiple-round dialogue and the performance is perfect.
2) Supports OCR and the performance is perfect.
3) Supports picture content recommendation, and the recommended pictures are highly relevant.
4) Supports the ability to construct, use, and maintain a knowledge graph. |
+
+### 9.1 Speech recognition
+
+This indicator is to test whether the intelligent customer service has speech recognition capability. This is the ability to test the accuracy of the intelligent customer service's speech recognition mainly through the technical test method. Through recognition and understanding, the voice signal is converted into corresponding text or commands.
+
+Evaluation methods:
+
+- Construct a speech data set, obtain the text of speech recognition, and separately count the word accuracy and sentence accuracy of speech recognition.
+- Word error rate (WER): Compare the recognized sequence with the label sequence of characters, insert, replace, and delete the total number of characters, divided by the percentage of the total number of words in the label sequence. Each test data will get a word error rate, and the average value is the word error rate of the test set.
+
+$$WER = \frac{NW_{misrecognized}}{NW_{total}}$$
+
+$NW_{misrecognized}$ : the number of misrecognized words.
+
+$NW_{total}$ : Total words.
+
+- c) Sentence error rate (SER): If there is a misrecognition of a word or character in a sentence, the sentence is considered to be misrecognized. The number of sentence recognition errors divided by the total number of sentences is the sentence error rate.
+
+$$SER = \frac{NS_{misrecognized}}{NS_{total}}$$
+
+$NS_{misrecognized}$ : the number of misrecognized sentences.
+
+$NS_{total}$ : Total sentences.
+
+### 9.2 Text to speech
+
+This indicator is to test whether the intelligent customer service has text to speech capability. This is the ability to convert any text into speech with a high degree of naturalness.
+
+Evaluation methods:
+
+- a) After the multi-round call task initiated by the outbound call system under test is completed, the text and audio are extracted.
+- b) Many testers use the mean opinion score (MOS) indicators (five-point scale) to rate the naturalness of the robot's speech synthesis in audio. The MOS scoring instructions can be seen in Table 4.
+
+**Table 4 – MOS scoring instructions**
+
+| Scores | Levels | Description |
+|--------|-----------|-----------------------------------------------------------------------------------------------------|
+| 5 | Excellent | Fluent and natural, can be completely relaxed, no need for attention. |
+| 4 | Good | The distortion is not obvious and requires attention, but does not need to be clearly concentrated. |
+| 3 | General | It is clearly distorted and requires a moderate level of attention; |
+| 2 | Bad | Severe distortion and need for concentration. |
+| 1 | Very bad | The quality of the speech is so poor that it is difficult to understand even if you try to listen. |
+
+- c) In the case of artificial recording and speech synthesis audio splicing, the overall fluency is required to be determined and the jumping and non-smooth conditions are required to be recorded.
+- d) In order to reflect the customizability and diversity of speech synthesis dialogue in the external call process, the situation regarding the richness of timbre and variety is to be recorded.
+
+### 9.3 Single-round dialogue
+
+Evaluate whether the intelligent customer service product has the capability of single-round conversation. A single round of conversation refers to a simple question and answer. The question can be described in one sentence and does not depend on the context.
+
+Evaluation methods:
+
+- a) A single round of dialogue test data set is used to observe the dialogue and question answering effects of intelligent customer service.
+- b) The recognition situation is divided into: accurate recognition, fuzzy recommendation is correct, fuzzy recommendation is wrong, not recognized.
+- c) Accurate recognition and fuzzy recommendation are regarded as successful intention recognition. The ratio of successful recognition to total tests is the intention recognition rate. The ratio of accurate recognition to total tests is the accurate recognition rate.
+
+$$\text{Intent recognition rate} = \frac{NT_{\text{true\&vague}}}{NT_{\text{total}}}$$
+
+$NT_{\text{true\&vague}}$ : *Accurately identify or indistinctly recommend the correct quantity*
+
+$NT_{\text{total}}$ : *Total task*
+
+$$\text{Accurate recognition rate} = \frac{NT_{\text{true}}}{NT_{\text{total}}}$$
+
+$NT_{\text{true}}$ : *The number of accurate identifications.*
+
+### 9.4 Multi-round dialogue
+
+This indicator is to evaluate the ability of intelligent customer service products to support multiple rounds of dialogue. In the customer service scenario, many problems cannot be solved by simple question and answer in a single round of conversation. When the user's needs are more complex and may need to be presented in multiple rounds of conversation, the machine can help the user find satisfactory results by asking, clarifying, or confirming. Such a round-trip interactive session is called the multi-round dialogue.
+
+Evaluation methods:
+
+- a) Use multiple rounds of dialogue to test the data sets. Before the intelligent customer service product gives the user accurate results, the system will ask diverging questions, add details and repeatedly ask questions based on the results to see whether it can be accurately identified.
+- b) Multiple rounds of test data sets covering 2-4 rounds.
+- c) All rounds of multiple dialogues were successfully identified as task completion, and the ratio of test data volume to task completion rate is given by:
+
+$$\text{Task completion rate} = \frac{T_{\text{completed}}}{T_{\text{total}}}$$
+
+$T_{\text{completed}}$ : *the number of completed tasks.*
+
+$T_{\text{total}}$ : *the total number of tasks.*
+
+- d) The ratio of the number of successful rounds identified in the multi-round test to the total number of test rounds is the recognition rate:
+
+$$\text{Recognition rate} = \frac{T_{\text{co-i}}}{T_{\text{total}}}$$
+
+$T_{\text{co-i}}$ : *The number of correctly identified multi – round dialogues.*
+
+### 9.5 Knowledge graph
+
+The purpose of this indicator is to evaluate whether the ICSS has the ability to construct, use, and maintain a knowledge graph. The ICSS can optionally have the ability to construct a knowledge graph, and can improve the functions lacking in the traditional knowledge base.
+
+Evaluation methods:
+
+- Determine whether the ICSS has the ability to build a knowledge graph through material reviews.
+- Test the ability of ICSS to build, generate and maintain knowledge graph through technical means.
+- Comprehensive evaluation of the construction, generation and maintenance of knowledge graphs and other indicators to determine whether customer service products have integrated knowledge graph technology.
+
+### 9.6 Multilingual interaction
+
+This indicator is to evaluate whether the ICSS has the ability to interact in multiple languages. The intelligent customer service can optionally have the ability of multilingual interaction, that is, the function of bilingual conversion can be automatically performed by machine translation.
+
+Evaluation methods:
+
+- Judge whether the ICSS is capable of multi-language interaction through material reviews.
+- Test the intelligibility of multilingual interaction of the ICSS and bilingual evaluation understudy (BLEU) score through test corpus.
+
+### 9.7 Optical character recognition
+
+The purpose of this indicator is to evaluate whether the ICSS has the capability of text image recognition. The ICSS can optionally have intelligent visual capabilities such as OCR to assist the ICSS in receiving and processing multi-modal user input.
+
+Evaluation methods:
+
+- Judge whether the ICSS has the capability of image and text recognition through material review.
+- Through the building of text image data to test whether the ICSS has text image recognition capability.
+
+$$Accuracy\ rate = \frac{Ima_{correctly}}{T_{total}}$$
+
+*Imacorrectly: The number of correctly identified images.*
+
+### 9.8 Picture content recommendation
+
+This indicator is to evaluate whether the ICSS has the ability to recommend related content of pictures. The ICSS can optionally identify pictures and recommend the same or similar items in specific fields such as e-commerce.
+
+Evaluation methods:
+
+- Judge whether the ICSS has the ability to recommend related pictures through material review.
+- Test whether the ICSS has the ability to recommend related contents of pictures by building image data, and score the relevancy of pictures on a scale of 0-5.
+
+## 10 ICSS system maturity
+
+Indicators of maturation of the ICSS system include data visibility, usability, reliability, security, maintainability, and auditability. The intelligence level description of this dimension can be seen in Table 5.
+
+**Table 5 – Intelligence levels for ICSS system maturation**
+
+| Intelligence levels | Description |
+|---------------------|--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+| Level-1 | 1) The usability performance is poor, the user's experience is poor.
2) The security performance is poor, the user's experience is poor. |
+| Level-2 | New relatives to the previous level:
1) The usability performance is general, and the user experience is basically acceptable.
2) The reliability performance is general.
3) The security performance is good, and the user experience is basically acceptable.
4) Supports auditability. |
+| Level-3 | New relatives to the previous level:
1) The usability performance is good.
2) The reliability performance is good.
3) The security performance is perfect.
4) Supports data visibility function, which can generate visual reports for business data in real time. |
+| Level-4 | New relatives to the previous level:
1) The usability performance is excellent.
2) The reliability performance is excellent, such as weather and news inquiries.
3) Supports auditability.
4) Supports automatic operation and maintenance.
5) Supports data visibility function, and the system can automatically generate analysis results and documents and export them. |
+| Level-5 | New relatives to the previous level:
1) Supports operation monitoring, and the system can quickly locate system operation problems. |
+
+## 10.1 Data visibility
+
+Enterprises need to judge the effect of intelligent customer service through visual analysis. The ICSS is required to have a report analysis function to help enterprises improve their operating efficiency.
+
+Evaluation methods:
+
+- a) Generate visual reports.
+- b) Analyse according to the report.
+- c) Export reports and data.
+
+### 10.2 Usability
+
+Evaluate whether the ICSS is easy to use. The ICSS is required to obey the principles of user friendliness and ease of use.
+
+Evaluation methods:
+
+- a) The reply message is required to be completed within a certain time, and there is a prompt such as "reply in customer service".
+- b) User-centred design. Used smoothly in a set of business processes in a guided manner.
+- c) Interface design can optionally fully consider the user experience, friendly and clear, simple operation, obvious function points. The main functions are required to be in a prominent position, and the commonly used functions are required to be in a position easy to operate. Remove the redundant steps and get to the result.
+
+## **10.3 Reliability**
+
+Evaluate whether the ICSS is mature and reliable. A mature and stable system is very important for the continuous operation of the ICSS.
+
+Evaluation methods:
+
+- a) Stable and reliable mature technology is required to be adopted to ensure the long-term safe operation of the system.
+- b) The hardware, software and information resources in the system can optionally meet the requirements of reliability design.
+- c) The system has fault-tolerant ability, which makes management and maintenance more convenient.
+- d) Unified planning and analysis of network design, selection, installation, debugging and other links to ensure reliable operation of the system.
+- e) The system provides multi-level security control means, establishes a perfect security management system, guarantees data security and PII protection and integrity, and simultaneously has reliable anti-virus measures.
+- f) System failure recovery capability.
+- g) Log management function.
+- h) System disaster recovery backup.
+
+### **10.4 Security**
+
+Evaluate the security of the ICSS. While providing intelligent services, intelligent customer service products must also ensure data security and legality of dialogues.
+
+Evaluation methods:
+
+- a) User program security and PII protection, including user permissions, password management, and so on.
+- b) System network security, including attack protection, vulnerability detection, Trojan killing, and so on.
+- c) Database security, including backup, data encryption, and so on.
+- d) Transmission security, including data encryption transmission, and so on.
+- e) Content security, including disabled word filtering, image filtering, and so on.
+- f) Deployment of security, including the separation of the two networks, export protection, wall protection, and so on.
+
+### **10.5 Maintainability**
+
+Evaluate the maintainability of the intelligent customer service system. The ICSS is required to have complete maintenance tools.
+
+Evaluation methods:
+
+- a) Whether to have automatic operation and maintenance technology.
+- b) Whether there is operation monitoring.
+
+### 10.6 Auditability
+
+Evaluate whether the ICSS is auditable. The operation data of the ICSS is required to be able to be checked, reviewed and traced.
+
+Evaluation methods:
+
+- a) Supports personnel authority management.
+- b) Supports operation audit.
+
+## 11 Service experience of enterprises
+
+Service experience of enterprises evaluation includes data access ability, human intervention ability, emotional pacification ability, assistant service ability, customer satisfaction. The intelligence levels description of this dimension can be seen in Table 6.
+
+**Table 6 – Intelligent levels for service experience of enterprises**
+
+| Intelligence levels | Description |
+|---------------------|----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+| Level-1 | - 1) Supports access to user information, and provides targeted services for users.
- 2) Supports manual intervention to deal with emergencies.
- 3) The user is not satisfied, and the total user experience score is [0, 60).
|
+| Level-2 | New relatives to the previous level:
- 1) Supports the manual intervention of the single-round dialogue, and the manual intervention rate is high.
- 2) The user is basically satisfied, and the total user experience score is [60, 70).
|
+| Level-3 | New relatives to the previous level:
- 1) Supports data access ability, and the data access rate is high.
- 2) Supports the manual intervention of the single-round dialogue, and the manual intervention rate is acceptable.
- 3) Supports the manual intervention of the multi-round dialogue, with a high rate of manual intervention.
- 4) The user is relatively satisfied, and the total user experience score is [70, 80).
|
+| Level-4 | New relatives to the previous level:
- 1) Supports the manual intervention of multiple rounds of dialogue, and the manual intervention rate is acceptable.
- 2) Supports assistant service ability.
- 3) The user is very satisfied, and the total user experience score is [80, 90).
|
+| Level-5 | New relatives to the previous level:
- 1) Supports emotional pacification ability, and switches to manual customer service for pacification when necessary.
- 2) The user is completely satisfied, and the total user experience score is [90, 100].
|
+
+### 11.1 Data access ability
+
+The purpose of this indicator is to evaluate whether smart customer service products can access user information and access capabilities. The intelligent customer service has data access capabilities, which can provide users with a more convenient and safe service experience.
+
+Evaluation methods:
+
+- a) Businesses that need access to data build a test suite to observe data access.
+- b) The data access rate is the number of successful implementations divided by the number of tests.
+
+$$\text{Data access rate} = \frac{T_{\text{successful}}}{T_{\text{total}}}$$
+
+$T_{\text{successful}}$ : successful data access.
+
+### 11.2 Human intervention ability
+
+This indicator is to evaluate the manual intervention of the ICSS and in order to judge the autonomous business capabilities of the intelligent customer service. In the process of providing services to users, the ICSS needs to rely on the intervention of manual customer service for specific items such as puzzles, serious questions, and user's mood swings.
+
+Evaluation methods:
+
+- a) Count the number of manual interventions during the single-round dialogue and multi-round dialogue testing.
+
+$$\text{Manual intervention rate} = \frac{T_{\text{manual}}}{T_{\text{total}}}$$
+
+$T_{\text{manual}}$ : the number of human interventions.
+
+### 11.3 Emotional pacification ability
+
+This indicator is to evaluate whether the ICSS can identify the user's mood swings and provide timely and effective pacification. Emotional pacification is a high-level demand for an ICSS, which requires the system to correctly determine the user's emotions through a series of elements such as speech, tone, wording, punctuation and tone words during the interaction with the user. When recognizing the user's emotions such as expressions of anger, it can respond and comfort in time, and if necessary, it can switch to manual customer service for pacification.
+
+Evaluation methods:
+
+- a) A corpus of anger and requests for artificial service was designed to evaluate the capability of providing emotional consolation.
+
+### 11.4 Assistant service ability
+
+This indicator is to assess whether the ICSS provides assistant services such as weather inquiries and news inquiries. The intelligent customer service needs to provide related services such as weather inquiries and news inquiries while providing business-related services.
+
+Evaluation methods:
+
+- a) Determine whether the ICSS has the related business ability to provide assistant services through material review.
+- b) Build the command corpus related to weather inquiry, news inquiry, etc., to test whether the ICSS has relevant abilities. The service ability of assistants is rated according to 0-5 score.
+
+## 11.5 Customer satisfaction
+
+This indicator is to test the effect of the user experience of the ICSS. The quality of the user experience directly determines whether the intelligent customer service can play the role of respondent on a certain product or on certain types of products. User experience is a purely subjective feeling established by users during the use of products. For any intelligent customer service product, the user experience comprehensively reflects the subjective experience of the system in terms of channel management, technical effects, and interface design. In the context of user-centred and people-oriented product design concepts, user experience has become a key indicator for evaluating the merits of human-computer interaction systems.
+
+Evaluation methods:
+
+- a) Through the investigation and trial of the ICSS, the user experience effect is assessed. The scoring indicators are as follows:
+- b) Useful: The ICSS is required to be useful and actually solve the user's problems and confusion.
+- c) Findable: Good navigation and positioning of elements is required to be provided so that users can quickly find the interactive entry point of intelligent customer service.
+- d) Accessible: The basic and common functions of the intelligent customer service are required to be accessible to all users, including members and non-members.
+- e) Desirable: Intelligent customer service is required to satisfy users' various emotional experiences, including emotional comfort, etc.
+- f) Credible: Intelligent customer service replies can let the user trust the system, no false forged information.
+- g) Each of the five specific indicators above gets 20 points, and the sum of the five items $S$ is the total score of user experience.
+- h) The total user experience score is 4 points, $S \in [0, 60)$ no score, $S \in [60, 70)$ 1 score, $S \in [70, 80)$ 2 score, $S \in [80, 90)$ 3 score, $S \in [90, 100]$ 4 score.
+- i) Researchers questioned: The rating group shall be composed of a variety of social roles and professionals and shall exceed 100 persons; Each person will score the ICSS independently, and the average score will be the final score of each system.
+
+
+
+## SERIES OF ITU-T RECOMMENDATIONS
+
+| | |
+|-----------------|-----------------------------------------------------------------------------------------------------------------------------------------------------------|
+| Series A | Organization of the work of ITU-T |
+| Series D | Tariff and accounting principles and international telecommunication/ICT economic and policy issues |
+| Series E | Overall network operation, telephone service, service operation and human factors |
+| Series F | Non-telephone telecommunication services |
+| Series G | Transmission systems and media, digital systems and networks |
+| Series H | Audiovisual and multimedia systems |
+| Series I | Integrated services digital network |
+| Series J | Cable networks and transmission of television, sound programme and other multimedia signals |
+| Series K | Protection against interference |
+| Series L | Environment and ICTs, climate change, e-waste, energy efficiency; construction, installation and protection of cables and other elements of outside plant |
+| Series M | Telecommunication management, including TMN and network maintenance |
+| Series N | Maintenance: international sound programme and television transmission circuits |
+| Series O | Specifications of measuring equipment |
+| Series P | Telephone transmission quality, telephone installations, local line networks |
+| Series Q | Switching and signalling, and associated measurements and tests |
+| Series R | Telegraph transmission |
+| Series S | Telegraph services terminal equipment |
+| Series T | Terminals for telematic services |
+| Series U | Telegraph switching |
+| Series V | Data communication over the telephone network |
+| Series X | Data networks, open system communications and security |
+| Series Y | Global information infrastructure, Internet protocol aspects, next-generation networks, Internet of Things and smart cities |
+| Series Z | Languages and general software aspects for telecommunication systems |
\ No newline at end of file
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+
+
+# Recommendation **ITU-T F.746.17 (12/2022)**
+
+SERIES F: Non-telephone telecommunication services
+Multimedia services
+
+## --- **Requirements for media processing services**
+
+
+
+The logo of the International Telecommunication Union (ITU) is located in the bottom right corner. It features a blue globe with white lines representing latitude and longitude, and the letters 'ITU' in a bold, blue, sans-serif font superimposed on the globe.
+
+ITU logo
+
+## ITU-T F-SERIES RECOMMENDATIONS **NON-TELEPHONE TELECOMMUNICATION SERVICES**
+
+### **TELEGRAPH SERVICE**
+
+| | |
+|-----------------------------------------------------------------|-------------|
+| Operating methods for the international public telegram service | F.1–F.19 |
+| The gentex network | F.20–F.29 |
+| Message switching | F.30–F.39 |
+| The international telemessages service | F.40–F.58 |
+| The international telex service | F.59–F.89 |
+| Statistics and publications on international telegraph services | F.90–F.99 |
+| Scheduled and leased communication services | F.100–F.104 |
+| Phototelegraph service | F.105–F.109 |
+
+### **MOBILE SERVICE**
+
+| | |
+|--------------------------------------------------------|-------------|
+| Mobile services and multdestination satellite services | F.110–F.159 |
+|--------------------------------------------------------|-------------|
+
+### **TELEMATIC SERVICES**
+
+| | |
+|-------------------------------------------|-------------|
+| Public facsimile service | F.160–F.199 |
+| Teletex service | F.200–F.299 |
+| Videotex service | F.300–F.349 |
+| General provisions for telematic services | F.350–F.399 |
+
+### **MESSAGE HANDLING SERVICES**
+
+F.400–F.499
+
+### **DIRECTORY SERVICES**
+
+F.500–F.549
+
+### **DOCUMENT COMMUNICATION**
+
+| | |
+|--------------------------------------|-------------|
+| Document communication | F.550–F.579 |
+| Programming communication interfaces | F.580–F.599 |
+
+### **DATA TRANSMISSION SERVICES**
+
+F.600–F.699
+
+### **MULTIMEDIA SERVICES**
+
+**F.700–F.799**
+
+### **ISDN SERVICES**
+
+F.800–F.849
+
+## **UNIVERSAL PERSONAL TELECOMMUNICATION**
+
+F.850–F.899
+
+## **ACCESSIBILITY AND HUMAN FACTORS**
+
+F.900–F.999
+
+*For further details, please refer to the list of ITU-T Recommendations.*
+
+# Recommendation ITU-T F.746.17
+
+## Requirements for media processing services
+
+## Summary
+
+Recommendation ITU-T F.746.17 identifies the functional requirements for the media processing services. In particular, the scope of this Recommendation includes functional requirements and application scenarios. Media processing services utilize a set of techniques including cloud computing, computing resource virtualization, and job queue processing to dynamically control and manage computing resources which improves scalability, flexibility and availability. This Recommendation specifies the functional requirements of general requirements, service provision requirements, service management requirements, security considerations, etc.
+
+## History
+
+| Edition | Recommendation | Approval | Study Group | Unique ID* |
+|---------|----------------|------------|-------------|---------------------------------------------------------------------------|
+| 1.0 | ITU-T F.746.17 | 2022-12-14 | 16 | 11.1002/1000/15191 |
+
+### Keywords
+
+Artificial intelligence (AI), audio processing, content delivery network (CDN), media processing service (MPS), video services.
+
+---
+
+\* To access the Recommendation, type the URL in the address field of your web browser, followed by the Recommendation's unique ID. For example, .
+
+## FOREWORD
+
+The International Telecommunication Union (ITU) is the United Nations specialized agency in the field of telecommunications, information and communication technologies (ICTs). The ITU Telecommunication Standardization Sector (ITU-T) is a permanent organ of ITU. ITU-T is responsible for studying technical, operating and tariff questions and issuing Recommendations on them with a view to standardizing telecommunications on a worldwide basis.
+
+The World Telecommunication Standardization Assembly (WTSA), which meets every four years, establishes the topics for study by the ITU-T study groups which, in turn, produce Recommendations on these topics.
+
+The approval of ITU-T Recommendations is covered by the procedure laid down in WTSA Resolution 1.
+
+In some areas of information technology which fall within ITU-T's purview, the necessary standards are prepared on a collaborative basis with ISO and IEC.
+
+## NOTE
+
+In this Recommendation, the expression "Administration" is used for conciseness to indicate both a telecommunication administration and a recognized operating agency.
+
+Compliance with this Recommendation is voluntary. However, the Recommendation may contain certain mandatory provisions (to ensure, e.g., interoperability or applicability) and compliance with the Recommendation is achieved when all of these mandatory provisions are met. The words "shall" or some other obligatory language such as "must" and the negative equivalents are used to express requirements. The use of such words does not suggest that compliance with the Recommendation is required of any party.
+
+## INTELLECTUAL PROPERTY RIGHTS
+
+ITU draws attention to the possibility that the practice or implementation of this Recommendation may involve the use of a claimed Intellectual Property Right. ITU takes no position concerning the evidence, validity or applicability of claimed Intellectual Property Rights, whether asserted by ITU members or others outside of the Recommendation development process.
+
+As of the date of approval of this Recommendation, ITU had not received notice of intellectual property, protected by patents/software copyrights, which may be required to implement this Recommendation. However, implementers are cautioned that this may not represent the latest information and are therefore strongly urged to consult the appropriate ITU-T databases available via the ITU-T website at .
+
+© ITU 2023
+
+All rights reserved. No part of this publication may be reproduced, by any means whatsoever, without the prior written permission of ITU.
+
+## Table of Contents
+
+###### Page
+
+| | | |
+|------|-------------------------------------------------|----|
+| 1 | Scope ..... | 1 |
+| 2 | References..... | 1 |
+| 3 | Definitions ..... | 1 |
+| 3.1 | Terms defined elsewhere ..... | 1 |
+| 3.2 | Terms defined in this Recommendation..... | 1 |
+| 4 | Abbreviations and acronyms ..... | 1 |
+| 5 | Conventions ..... | 2 |
+| 6 | Introduction ..... | 3 |
+| 7 | Overview of media processing services ..... | 3 |
+| 8 | Requirements ..... | 5 |
+| 8.1 | General requirements..... | 5 |
+| 8.2 | Service provision requirements ..... | 5 |
+| 8.3 | Availability and scalability requirements ..... | 6 |
+| 8.4 | Service management requirements..... | 6 |
+| 9 | Security considerations..... | 7 |
+| | Appendix I – Application scenarios..... | 8 |
+| I.1 | Face filtering..... | 8 |
+| I.2 | Audio processing..... | 8 |
+| I.3 | Watermarks..... | 8 |
+| I.4 | Specific content detection..... | 8 |
+| I.5 | Information insertion ..... | 8 |
+| I.6 | Video tagging ..... | 8 |
+| I.7 | Speech recognition ..... | 8 |
+| I.8 | SD to HD conversion..... | 8 |
+| I.9 | Video smart cover..... | 8 |
+| I.10 | Video format converting..... | 8 |
+| I.11 | Resolution enhancement..... | 9 |
+| I.12 | Video clipping and stitching..... | 9 |
+| I.13 | Picture in picture (PIP) ..... | 9 |
+| I.14 | Encrypting video ..... | 9 |
+| | Bibliography..... | 10 |
+
+
+
+# Requirements for media processing services
+
+# 1 Scope
+
+This Recommendation identifies the requirements for media processing services. In particular, the scope of this Recommendation includes functional requirements and application scenarios.
+
+# 2 References
+
+The following ITU-T Recommendations and other references contain provisions which, through reference in this text, constitute provisions of this Recommendation. At the time of publication, the editions indicated were valid. All Recommendations and other references are subject to revision; users of this Recommendation are therefore encouraged to investigate the possibility of applying the most recent edition of the Recommendations and other references listed below. A list of the currently valid ITU-T Recommendations is regularly published. The reference to a document within this Recommendation does not give it, as a stand-alone document, the status of a Recommendation.
+
+None.
+
+# 3 Definitions
+
+### 3.1 Terms defined elsewhere
+
+This Recommendation uses the following terms defined elsewhere:
+
+**3.1.1 artificial intelligence (AI)** [b-ITU-T F.749.13]: An interdisciplinary field, usually regarded as a branch of computer science, dealing with models and systems for the performance of functions generally associated with human intelligence, such as reasoning and learning.
+
+**3.1.2 cloud computing** [b-ITU-T Y.3500]: Paradigm for enabling network access to a scalable and elastic pool of shareable physical or virtual resources with self-service provisioning and administration on-demand.
+
+**3.1.3 content delivery network (CDN)** [b-ITU-T F.750]: A network optimized for delivering digital content.
+
+**3.1.4 platform as a service (PaaS)** [b-ITU-T Y.3500]: Cloud service category (see clause 3.2.10) in which the cloud capabilities type (see clause 3.2.4 in [b-ITU-T Y.3500]) provided to the cloud service customer (see clause 3.2.11 in [b-ITU-T Y.3500]) is a platform capabilities type (see clause 3.2.31 in [b-ITU-T Y.3500]).
+
+### 3.2 Terms defined in this Recommendation
+
+This Recommendation defines the following term:
+
+**3.2.1 media processing service (MPS)**: A cloud service for transcoding multimedia data, which can provide a cost-effective, easy-to-use, elastic, and highly scalable method to convert audio and video into formats suitable for playing on PCs, TVs and mobile interfaces, and can also conduct deep learning based technology on massive data to analyse the content including text, voice and other scenarios of the media in multiple modes, and to achieve intelligent review, content understanding, intelligent editing, etc.
+
+# 4 Abbreviations and acronyms
+
+This Recommendation uses the following abbreviations and acronyms:
+
+| | |
+|----------|--------------------------------------------------------------------------|
+| 3GP | 3rd Generation Partnership Project (3GPP) file format |
+| AI | Artificial Intelligence |
+| AR | Augmented Reality |
+| ASIC | Application Specific Integrated Circuit |
+| AVI | Audio Video Interleaved |
+| CDN | Content Delivery Network |
+| CPU | Central Processing Unit |
+| DAG | Direct Acyclic Graph |
+| DRM | Digital Rights Management |
+| FLV | Flash Video |
+| FPGA | Field Programmable Gate Array |
+| GPU | Graphics Processing Unit |
+| HD | High-Definition |
+| IO | Input/Output |
+| M3U8 | Moving Picture Experts Group Audio Layer 3 Uniform Resource Locator-UTF8 |
+| MP4 | Moving Picture Experts Group 4 |
+| MPG/MPEG | Moving Picture Experts Group |
+| MPS | Media Processing Service |
+| PaaS | Platform as a Service |
+| PGC | Professionally Generated Content |
+| PIP | Picture in Picture |
+| SD | Standard-Definition |
+| UGC | User Generated Content |
+| URL | Uniform Resource Locator |
+| UTF-8 | Unicode Transformation Format |
+| VR | Virtual Reality |
+
+# 5 Conventions
+
+In this Recommendation:
+
+- The keywords "is required to" indicate a requirement which must be strictly followed and from which no deviation is permitted if conformance to this document is to be claimed.
+- The keywords "is recommended" indicate a requirement which is recommended but which is not absolutely required. Thus, this requirement needs not be present to claim conformance.
+- The keywords "can optionally" and "may" indicate an optional requirement which is permissible, without implying any sense of being recommended. These terms are not intended to imply that the vendor's implementation must provide the option and the feature can be optionally enabled by the network operator/service provider. Rather, it means the vendor may optionally provide the feature and still claim conformance with the specification.
+
+# 6 Introduction
+
+With the development of Internet technology, the network traffic brought by multimedia content, especially audio and video services has had an explosive growth. Meanwhile, video services have been widely used in entertainment, finance, education, medical and other fields. 4K/8K and virtual reality (VR) / augmented reality (AR) video services will be popular. The rise of live broadcasting and short video services has driven the development of professionally generated content (PGC) and user generated content (UGC). With these massive media contents, how to provide superior service to ensure that media content can be distributed quickly, reliably, and safely is the most significant issue to be solved currently.
+
+Traditionally, content delivery network (CDN) is used to deliver content from the head-end of content sources to the terminal devices. CDN only transmits media content without any processing. With these requirements of new video services, media contents are required to be processed before transmission through the CDN. For example, media contents are required to be transcoded adaptively according to the quality of the network. UGC contents should not contain specific features. Some image and text contents are required to be detected, located, and identified to provide personalized service for consumers.
+
+Regarding the huge amount of video data and the variety of media processing, the way of processing in the local computing system cannot meet the current computing resource requirements of video services. At present, computing technology is widely applied. Media processing services are based on the concept of cloud computing technology. Media processing services provide a cost-effective, easy-to-use, elastic, on-demand, and highly scalable method to process audio and video in various video services.
+
+In a typical media processing service flow from end to end, video contents are captured by the content provider. After the video is uploaded to the cloud server, media processing services begin to work. In order to adapt to different network environments and terminals, the video will be usually transcoded in the cloud. Some personalized value-added services are provided, which include data statistics service, content review service, real-time watermarking service and so on. After media processing, the video contents are distributed and speeded up to the terminal devices by the CDN. Video contents are decoded and played on the terminal devices.
+
+Figure 6-1 shows the reference model for media processing services (MPSs).
+
+
+
+F.746.17(22)
+
+Figure 6-1 – Reference model for media processing services. The diagram illustrates a sequential flow from left to right: Video capture (by Content provider) -> Video coding -> Video processing (containing Watermarks, Face filters, Video tagging, Specific content detection, Information insertion, Speech recognition, and ellipsis) -> Content distributing (by CDN) -> Video decoding -> Video playing (by Content consumer). Below the flow, three large chevrons group these steps into 'Video provider' (capture and coding), 'Video service' (processing), and 'Video display' (distributing, decoding, and playing). A small code 'F.746.17(22)' is in the bottom right corner.
+
+**Figure 6-1 – Reference model for media processing services**
+
+# 7 Overview of media processing services
+
+Media processing services utilize a set of techniques including cloud computing, computing resource virtualization, and job queue processing to dynamically control and manage various computing resources, which improves scalability, flexibility and availability.
+
+Figure 7-1 illustrates the typical framework of media processing services.
+
+
+
+The diagram illustrates the typical framework of media processing services, organized into three main layers of management and resource allocation:
+
+- Service management:** Connected to a grid of media processing services including Face filters, Audio processing, Watermarks, Specific content detection, Information insertion, Video tagging, Speech recognition, SD to HD conversion, and others (...).
+- Job management:** Connected to a queueing system where jobs (Job1, Job2, Job3) enter from an "Enter queue" and exit through an "Exit queue".
+- Resource management:** Connected to the "Logical partition", "Virtual resource", and "Physical resource" layers. It also has a bidirectional connection to "Job management".
+
+The flow of data and jobs is as follows: Service management provides services to the job queue. Jobs enter the queue, are assigned to a logical partition, then to virtual resources, and finally to physical resources for processing. Resource management oversees the allocation of virtual and physical resources to the logical partitions.
+
+F.746.17(22)
+
+Figure 7-1: Typical framework of media processing services. The diagram shows a hierarchical structure of management and resource layers. At the top, Service management is connected to a grid of media processing services including Face filters, Audio processing, Watermarks, Specific content detection, Information insertion, Video tagging, Speech recognition, and SD to HD conversion. Below this, Job management is connected to a queueing system with Job1, Job2, and Job3 entering from an 'Enter queue' and exiting through an 'Exit queue'. These jobs are then processed through three layers: Logical partition (represented by colored ovals), Virtual resource (represented by server icons), and Physical resource (represented by server icons). Resource management is shown at the bottom, connected to the Virtual and Physical resource layers and also connected to Job management.
+
+**Figure 7-1 – Typical framework of media processing services**
+
+A typical media processing service generally consists of many physical resource nodes which are located in a resource pool supported by the cloud computing technology. The nodes are deployed as physical resources such as servers and storage which include many types of computing units, such as the central processing unit (CPU), graphics processing unit (GPU), field programmable gate array (FPGA), and the application specific integrated circuit (ASIC). These computing units are the main hardware to execute various media processing services. The physical resources are abstracted to the virtual resources such as virtual machines and virtual storage, which form a virtual resources pool utilizing virtualization technology. Computing units are virtualized into many virtual computing units. In order to provide service to multiple vendors, virtual resources and virtual computing units are aggregated and isolated according to the vendors' service requirements. Every logical partition is allocated to a specific job. Resource management capability is responsible to manage physical resources and virtualized resources.
+
+A job is a media processing job according to the vendor's requirements. A job consists of three main features which are input resources, media processing service type and parameters, and output video or data. Input resources are original media such as videos, files, or streams that vendors want to process. Media processing service types are mentioned in scenarios while parameters are set by the vendors according to their requirements. Output videos and data are products of media processing, which are various types or formats according to the requirements.
+
+Job management capability is responsible for managing the life span of a job. It is also responsible for job scheduling management, selecting computing resources, and logical partition to execute jobs based on workload and resource loads. Job scheduling can dispatch jobs to different queues for execution according to information such as media processing service type, job priority, submission time, etc.
+
+Service management capability is responsible for managing all kinds of media processing services. Service management provides a portal for vendors to select their services and set up parameters. Service management submits this information to the job management, job management then configures the related logical partitions and physical nodes, and executes the jobs by scheduling.
+
+The logical partition is managed by job management which controls and configures the logical partition in terms of the vendors' requirements. When the requirements of a logical partition are changing, job management requires resource management to perform functions such as adding or diminishing the virtual resources to the logical partition.
+
+# **8 Requirements**
+
+This clause addresses the requirements for media processing services.
+
+## **8.1 General requirements**
+
+Media processing service is a platform as a service (PaaS) service. It provides various types of services by concatenating or assembling various media related processing function modules. These related modules involve the mux layer, codec-stream layer, and transport protocol layer. It includes various processing conversions such as video image processing, audio processing, etc. All of these functions can be combined. Since each module requires different computing resources, network input/output (IO), storage, etc., thus different hardware environments required for each module need to be scheduled together for parallel or serial processing to meet the various functional requirements of users. Due to the inconsistent processing time of each function module, it may cause them to be influenced by each other. This could lead the entire processing link to be too long in time. Since some types of media processing services need more processing capabilities to be consumed than that of the common services, they can also meet the same efficiency requirements of the media processing. The system is recommended or required to provide the following capabilities:
+
+GR-01: The system is required to support the orchestration capability of the function modules based on the direct acyclic graph (DAG). By freely combining various processors, the functions could get integrity and variety.
+
+GR-02: The system is recommended to support the setting of the efficiency requirements of a certain function. For example, a 30-minute video can be processed within 5 minutes or 30 minutes.
+
+GR-03: The system is required to support heterogeneous capabilities to coordinate different types of devices to complete the same job, and to achieve a balance between performance and cost. Algorithms of media processing may be based on different computing units and hardware (such as CPU, GPU, FPGA, ASIC, etc.) It is necessary to complete specific processing sub-job by the corresponding computing units and hardware, and finally serially or parallel coordinate these processing results to complete a job.
+
+In general, the system is a distributed system, which is required to support streaming and parallel processing.
+
+## **8.2 Service provision requirements**
+
+SPR-01: The system is required to provide load-balance capability, which supports the concurrent processing of multiple jobs and avoid excessive load on a single hardware node, which affects the processing efficiency.
+
+SPR-02: The system is recommended to support elastic expansion and contraction of computing resources on time or on demand, thereby improving processing efficiency and reducing costs.
+
+SPR-03: The system is recommended to support grey releasing or upgrading among different versions. The version iteration cycle of cloud services is not fixed, and there are jobs running during release. In order to avoid the risk of potential defects introduced by the released version, which may cause the system to be fully affected, the grey releasing or upgrading can be performed in different arrangements such as groups, intervals, etc., and ways such as splitting dimensions on a user's importance/priorities, job function module, regions of service supporting/infrastructure, etc.
+
+SPR-04: The system is recommended to support the online job duplication ability for verification of functions. In order to ensure the stability of the version release and reduce the introduction of potential defects, A/B testing can be performed for online jobs and the test results can be compared. Some jobs may be suitable for running A/B testing both online, for an original job and offline for a duplicated job.
+
+SPR-05: The system is recommended to support cloud-native deployment capabilities with the container. It is convenient for operation, maintenance, management and control.
+
+SPR-06: The system is required to provide basic capabilities such as logging, end-to-end link inspection, capability usage / occupancy ratio monitoring and alarm, cost and billing, etc.
+
+## **8.3 Availability and scalability requirements**
+
+ASR-01: The system is required to provide unitized (in logical dimension) and rationalized (in physical dimension) deployment capabilities, and can provide high availability at the region-level (divided following service supporting / infrastructure, etc.) When an input file (such as a video segment) comes from region A with lower availability than region B where an MPS system is located, the availability of service after the MPS is processed may not be lower than that in region A. When the input file (such as a video segment) comes from region A with higher availability than region B where the MPS system is located, the availability will be the same as that in region B.
+
+ASR-02: The system is required to support extendibility and can dynamically expand or contract resources to quickly respond to service requirements when service scale quickly increases or decreases.
+
+ASR-03: The system is required to provide the alarm capability with pre-set values for alarm conditions or thresholds.
+
+ASR-04: The system is recommended to provide the back-off and degradation mechanism to ensure the stability of the basic functions for the services as far as possible under abnormal conditions.
+
+ASR-05: The system is recommended to support automatic or manual intervention for failed jobs, then get compensation via quick rerunning. It should prioritize the requirement to restore jobs from users as normal under a flexible strategy.
+
+## **8.4 Service management requirements**
+
+The system is required to provide capabilities such as operable, maintainable, management, control, configurable, traceable and troubleshooting.
+
+SMR-01: Operability, maintainability, manageability and controllability: It is required to include batch submission of jobs, job queue management (with job processing priority) and job cancellation, etc.
+
+SMR-02: Configurability: It is required to be changed only through configuration without modifying the hardware / software.
+
+SMR-03: Trackability: It is required to include the status of the overall capability usage / occupancy ratio and the status of specific jobs.
+
+SMR-04: Troubleshooting capability: According to the end-to-end link log, it is required to support the problem that could be located at the system-level and job-level.
+
+# **9 Security considerations**
+
+The system is required to provide security for accessing data. The address of the input video or output video processed by the system should be the address of the stored object bucket, rather than the uniform resource locator (URL) which is accessible on the public network, to ensure the security of the reading / writing data of the system.
+
+SC-01: The system is required to provide security for the storage service of data. The object storage service selected by the system should have permission configuration management and security control.
+
+SC-02: The system is required to provide security for the operation of the system. As a public cloud service, the system should have a unified account management system consistent with other cloud products and services so that it can build mechanisms such as account permission management, service subscribing or unsubscribing, and anti-attack.
+
+SC-03: The system is required to provide compliance for the user's service data. The system must not store the user's video content, and the logs related to the user's service data shall be accessed only within the specific area/region scope and must not be accessed across borders or areas/regions. The related log data should be cleared periodically. The alarm information related to the logs should also be desensitized.
+
+SC-04: The system is required to provide security for the operation and maintenance of the system itself. The core management and control application service of the system is the operation and maintenance system of the internal platform, which is separate from the public cloud management and control system. The internal operation and maintenance system should be operated under multi-role with different permission levels.
+
+SC-05: The system is recommended to provide encryption of the user's data. The system needs to provide an encryption (i.e., digital rights management (DRM)) function for video content, which can be used as content protection for distribution and playback.
+
+## Appendix I
+
+## Application scenarios
+
+(This appendix does not form an integral part of this Recommendation.)
+
+The typical service application scenarios for media processing services are the following.
+
+### **I.1 Face filtering**
+
+Face filtering service offers various filters and methods such as beautifying the facial features for anchors in the Internet broadcast services.
+
+### **I.2 Audio processing**
+
+Audio processing service offers audio mixing, in-ear monitoring, and other audio processing technologies for anchors in the Internet broadcast services.
+
+### **I.3 Watermarks**
+
+Watermarks service helps to add an identifying image or text as watermarks in the output video to safeguard video copyright for content providers.
+
+### **I.4 Specific content detection**
+
+Specific content detection service offers intelligent identification of specific content to reduce the risk of violations for content providers and users.
+
+### **I.5 Information insertion**
+
+Information insertion services can insert supplemental information in live streaming, which is suitable for live streaming quizzes, presentations, and other scenarios.
+
+### **I.6 Video tagging**
+
+Video tagging service offers the ability to provide video classification and multi-dimension content tags, which is suitable for personalized recommendation and searching services for content providers.
+
+### **I.7 Speech recognition**
+
+Speech recognition service offers multiple speech recognition solutions to transfer audio information into texts in various scenarios, such as meetings, courts and interviews.
+
+### **I.8 SD to HD conversion**
+
+Standard-definition (SD) to high-definition (HD) conversion service is able to convert standard-definition videos to high-definition videos by removing the compression noise of transcoding technology.
+
+### **I.9 Video smart cover**
+
+Video smart cover service offers an automatic capture of wonderful pictures such as the cover of the video content by artificial intelligence (AI) analysis, which can be applied to the automatic cover selection of new and old videos and improve the click rate and user experience of the video.
+
+### **I.10 Video format converting**
+
+In order to be compatible with different demands for video storage, transferring and playing, a video format converting service is needed. Video format includes a 3rd generation partnership project
+
+(3GPP) file format (3GP), audio video interleaved (AVI), flash video (FLV), moving picture experts group 4 (MP4), moving picture experts group audio layer 3 uniform resource locator – unicode transformation format (UTF-8) (M3U8), moving picture experts group (MPG/MPEG), etc.
+
+### **I.11 Resolution enhancement**
+
+The resolution of old historical videos is low. It is necessary to convert the low resolution of the original video into high resolution, which is called resolution enhancement.
+
+### **I.12 Video clipping and stitching**
+
+Video clipping and stitching service offers multiple videos to be edited, spliced, cut, and processed to make a new video programme.
+
+### **I.13 Picture in picture (PIP)**
+
+PIP service offers the service to embed one video as part of the frame into another video.
+
+### **I.14 Encrypting video**
+
+Encrypting video service offers an encrypted content to avoid specific downloading and disseminating. Services such as online education, paid video, and other paid contents use this service.
+
+## Bibliography
+
+- [b-ITU-T F.749.13] Recommendation ITU-T F.749.13 (2021), *Framework and requirements for civilian unmanned aerial vehicle flight control using artificial intelligence.*
+- [b-ITU-T F.750] Recommendation ITU-T F.750 (2005), *Metadata framework.*
+- [b-ITU-T Y.3500] Recommendation ITU-T Y.3500 (2014), *Information technology – Cloud computing – Overview and vocabulary.*
+
+
+
+## SERIES OF ITU-T RECOMMENDATIONS
+
+| | |
+|-----------------|-----------------------------------------------------------------------------------------------------------------------------------------------------------|
+| Series A | Organization of the work of ITU-T |
+| Series D | Tariff and accounting principles and international telecommunication/ICT economic and policy issues |
+| Series E | Overall network operation, telephone service, service operation and human factors |
+| Series F | Non-telephone telecommunication services |
+| Series G | Transmission systems and media, digital systems and networks |
+| Series H | Audiovisual and multimedia systems |
+| Series I | Integrated services digital network |
+| Series J | Cable networks and transmission of television, sound programme and other multimedia signals |
+| Series K | Protection against interference |
+| Series L | Environment and ICTs, climate change, e-waste, energy efficiency; construction, installation and protection of cables and other elements of outside plant |
+| Series M | Telecommunication management, including TMN and network maintenance |
+| Series N | Maintenance: international sound programme and television transmission circuits |
+| Series O | Specifications of measuring equipment |
+| Series P | Telephone transmission quality, telephone installations, local line networks |
+| Series Q | Switching and signalling, and associated measurements and tests |
+| Series R | Telegraph transmission |
+| Series S | Telegraph services terminal equipment |
+| Series T | Terminals for telematic services |
+| Series U | Telegraph switching |
+| Series V | Data communication over the telephone network |
+| Series X | Data networks, open system communications and security |
+| Series Y | Global information infrastructure, Internet protocol aspects, next-generation networks, Internet of Things and smart cities |
+| Series Z | Languages and general software aspects for telecommunication systems |
\ No newline at end of file
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+
+
+# Recommendation **ITU-T F.746.18 (06/2024)**
+
+SERIES F: Non-telephone telecommunication services
+Multimedia services
+
+---
+
+**Requirements for interactive low-latency
+multimedia transmission system over the
+Internet**
+
+
+
+The logo of the International Telecommunication Union (ITU) is located in the bottom right corner. It features a blue globe with white lines representing latitude and longitude, and the letters 'ITU' in a bold, blue, sans-serif font superimposed on the globe.
+
+ITU logo
+
+## ITU-T F-SERIES RECOMMENDATIONS **Non-telephone telecommunication services**
+
+| | |
+|-----------------------------------------------------------------|--------------------|
+| TELEGRAPH SERVICE | F.1-F.109 |
+| Operating methods for the international public telegram service | F.1-F.19 |
+| The gentex network | F.20-F.29 |
+| Message switching | F.30-F.39 |
+| The international telemessage service | F.40-F.58 |
+| The international telex service | F.59-F.89 |
+| Statistics and publications on international telegraph services | F.90-F.99 |
+| Scheduled and leased communication services | F.100-F.104 |
+| Phototelegraph service | F.105-F.109 |
+| MOBILE SERVICE | F.110-F.159 |
+| Mobile services and multdestination satellite services | F.110-F.159 |
+| TELEMATIC SERVICES | F.160-F.399 |
+| Public facsimile service | F.160-F.199 |
+| Teletex service | F.200-F.299 |
+| Videotex service | F.300-F.349 |
+| General provisions for telematic services | F.350-F.399 |
+| MESSAGE HANDLING SERVICES | F.400-F.499 |
+| DIRECTORY SERVICES | F.500-F.549 |
+| DOCUMENT COMMUNICATION | F.550-F.599 |
+| Document communication | F.550-F.579 |
+| Programming communication interfaces | F.580-F.599 |
+| DATA TRANSMISSION SERVICES | F.600-F.699 |
+| MULTIMEDIA SERVICES | F.700-F.799 |
+| ISDN SERVICES | F.800-F.849 |
+| UNIVERSAL PERSONAL TELECOMMUNICATION | F.850-F.899 |
+| ACCESSIBILITY AND HUMAN FACTORS | F.900-F.999 |
+
+*For further details, please refer to the list of ITU-T Recommendations.*
+
+# Recommendation ITU-T F.746.18
+
+# Requirements for interactive low-latency multimedia transmission system over the Internet
+
+## Summary
+
+Recommendation ITU-T F.746.18 specifies the functional requirements of interactive low-latency multimedia transmission system (ILMTS) over the Internet. It identifies the key functional requirements from the different aspects, such as service level, application level and management level. According to those requirements, this Recommendation also introduces a reference framework of ILMTS. Some use cases are described in the appendix.
+
+Service providers who provide the interactive live content delivery service with low-latency media delivery can design a standardized real-time multimedia service system by following the requirements defined in this Recommendation.
+
+## History \*
+
+| Edition | Recommendation | Approval | Study Group | Unique ID |
+|---------|----------------|------------|-------------|--------------------|
+| 1.0 | ITU-T F.746.18 | 2024-06-13 | 16 | 11.1002/1000/15907 |
+
+## Keywords
+
+Interactive, low latency, multimedia transmission.
+
+---
+
+\* To access the Recommendation, type the URL in the address field of your web browser, followed by the Recommendation's unique ID.
+
+## FOREWORD
+
+The International Telecommunication Union (ITU) is the United Nations specialized agency in the field of telecommunications, information and communication technologies (ICTs). The ITU Telecommunication Standardization Sector (ITU-T) is a permanent organ of ITU. ITU-T is responsible for studying technical, operating and tariff questions and issuing Recommendations on them with a view to standardizing telecommunications on a worldwide basis.
+
+The World Telecommunication Standardization Assembly (WTSA), which meets every four years, establishes the topics for study by the ITU-T study groups which, in turn, produce Recommendations on these topics.
+
+The approval of ITU-T Recommendations is covered by the procedure laid down in WTSA Resolution 1.
+
+In some areas of information technology which fall within ITU-T's purview, the necessary standards are prepared on a collaborative basis with ISO and IEC.
+
+### NOTE
+
+In this Recommendation, the expression "Administration" is used for conciseness to indicate both a telecommunication administration and a recognized operating agency.
+
+Compliance with this Recommendation is voluntary. However, the Recommendation may contain certain mandatory provisions (to ensure, e.g., interoperability or applicability) and compliance with the Recommendation is achieved when all of these mandatory provisions are met. The words "shall" or some other obligatory language such as "must" and the negative equivalents are used to express requirements. The use of such words does not suggest that compliance with the Recommendation is required of any party.
+
+## INTELLECTUAL PROPERTY RIGHTS
+
+ITU draws attention to the possibility that the practice or implementation of this Recommendation may involve the use of a claimed Intellectual Property Right. ITU takes no position concerning the evidence, validity or applicability of claimed Intellectual Property Rights, whether asserted by ITU members or others outside of the Recommendation development process.
+
+As of the date of approval of this Recommendation, ITU had not received notice of intellectual property, protected by patents/software copyrights, which may be required to implement this Recommendation. However, implementers are cautioned that this may not represent the latest information and are therefore strongly urged to consult the appropriate ITU-T databases available via the ITU-T website at .
+
+© ITU 2024
+
+All rights reserved. No part of this publication may be reproduced, by any means whatsoever, without the prior written permission of ITU.
+
+## Table of Contents
+
+###### Page
+
+| | | |
+|-----|----------------------------------------------------------------------------------------------------------|----|
+| 1 | Scope ..... | 1 |
+| 2 | References..... | 1 |
+| 3 | Definitions ..... | 1 |
+| 3.1 | Terms defined elsewhere ..... | 1 |
+| 3.2 | Terms defined in this Recommendation..... | 2 |
+| 4 | Abbreviations and acronyms ..... | 2 |
+| 5 | Conventions ..... | 2 |
+| 6 | Introduction ..... | 3 |
+| 7 | Requirements for interactive low-latency multimedia transmission system over the Internet..... | 4 |
+| 7.1 | Service requirements ..... | 4 |
+| 7.2 | Management requirements ..... | 4 |
+| 7.3 | Accounting requirements..... | 5 |
+| 7.4 | Networking requirements ..... | 5 |
+| 7.5 | Quality of Service (QoS) and performance requirements ..... | 5 |
+| 7.6 | Scalability requirements ..... | 5 |
+| 8 | Reference framework..... | 6 |
+| | Appendix I – Use cases for interactive low-latency multimedia transmission system over the Internet..... | 8 |
+| I.1 | E-commerce live broadcasting ..... | 8 |
+| I.2 | Multiparty visual meeting..... | 8 |
+| I.3 | Live distance learning..... | 8 |
+| I.4 | Video chat..... | 8 |
+| I.5 | Cloud games ..... | 8 |
+| I.6 | Cloud computer ..... | 9 |
+| I.7 | Cloud rendering..... | 9 |
+| | Bibliography..... | 10 |
+
+
+
+# Requirements for interactive low-latency multimedia transmission system over the Internet
+
+## 1 Scope
+
+This Recommendation defines the requirements for interactive low-latency multimedia transmission system (ILMTS) over the Internet, including service requirements, management requirements, accounting requirements, networking requirements, quality of service (QoS) and performance requirements, and scalability requirements, and specifies the use cases for the ILMTS.
+
+## 2 References
+
+The following ITU-T Recommendations and other references contain provisions, which, through reference in this text, constitute provisions of this Recommendation. At the time of publication, the editions indicated were valid. All Recommendations and other references are subject to revision; users of this Recommendation are therefore encouraged to investigate the possibility of applying the most recent edition of the Recommendations and other references listed below. A list of the currently valid ITU-T Recommendations is regularly published. The reference to a document within this Recommendation does not give it, as a stand-alone document, the status of a Recommendation.
+
+None.
+
+# 3 Definitions
+
+### 3.1 Terms defined elsewhere
+
+This Recommendation uses the following terms defined elsewhere:
+
+**3.1.1 cloud-edge collaboration** [b-ITU-T F.747.13]: A process (or method) that coordinates cloud computing and edge computing, dynamically allocates required computing, algorithm models, data, or other resources, and jointly completes the same tasks (or objectives) agreed in advance.
+
+**3.1.2 container** [b-ITU-T Y.3535]: A set of software to provide isolation, resource control and portability for virtualization processing of an application.
+
+NOTE 1 – A container runs on the kernel in a bare-metal machine or virtual machine.
+
+NOTE 2 – "Application" implies business logic including a required library or binary to run in a container.
+
+**3.1.3 control plane** [b-ITU-T Y.2011]: The set of functions that controls the operation of entities in the stratum or layer under consideration, plus the functions required to support this control (see clause 8.1.1 of ITU-T Y.2011 for some details).
+
+**3.1.4 data plane** [b-ITU-T Y.2011]: The set of functions used to transfer data in the stratum or layer under consideration.
+
+**3.1.5 microservice** [b-ITU-T J.1301]: An architectural and organizational approach to software development where software is composed of small independent microservices that communicate over well-defined application programming interfaces. Microservice architecture makes applications easier to scale and faster to develop, enabling innovation and accelerating time-to-market for new features.
+
+**3.1.6 microservice architecture** [b-ISO/IEC TS 23167]: Design approach that divides an application into a set of microservices.
+
+### 3.2 Terms defined in this Recommendation
+
+This Recommendation defines the following terms:
+
+**3.2.1 access scheduling:** A mechanism used to select the most appropriate network access point for a client according to its access request and network status.
+
+**3.2.2 cloud-edge-client collaboration:** An extended cloud-edge collaboration that involves clients or terminal devices as a participation part of a joint task processing.
+
+**3.2.3 container cloud:** A cloud computing platform based on container technology.
+
+**3.2.4 routing scheduling:** A mechanism used to select the optimal relay node and data forwarding path based on the network topology and network traffic status.
+
+**3.2.5 thin terminal:** A lightweight terminal device with limited local functions and capabilities for computing, whose applications and storage functions are mostly deployed remotely.
+
+## 4 Abbreviations and acronyms
+
+This Recommendation uses the following abbreviations and acronyms:
+
+| | |
+|-------|--------------------------------------------------------|
+| CDN | Content Delivery Network |
+| CPU | Central Processing Unit |
+| HLS | HTTP Live Streaming |
+| HTTP | Hypertext Transfer Protocol |
+| ILMTS | Interactive Low-Latency Multimedia Transmission System |
+| P2P | Peer-to-Peer |
+| PaaS | Platform as a Service |
+| QoS | Quality of Service |
+| RTMP | Real Time Messaging Protocol |
+| SLA | Service Level Agreement |
+| TCP | Transmission Control Protocol |
+| VM | Virtual Machine |
+| VoIP | Voice over Internet Protocol |
+| XR | Extended Reality |
+
+## 5 Conventions
+
+In this Recommendation:
+
+- The keywords "is required to" indicate a requirement which must be strictly followed and from which no deviation is permitted if conformance to this Recommendation is to be claimed.
+- The keywords "is recommended" indicate a requirement which is recommended but which is not absolutely required. Thus, this requirement need not be present to claim conformance.
+- The keywords "can optionally" and "may" indicate an optional requirement which is permissible, without implying any sense of being recommended. These terms are not intended to imply that the vendor's implementation must provide the option and the feature can be optionally enabled by the network operator/service provider. Rather, it means the vendor may optionally provide the feature and still claim conformance with the specification.
+
+# 6 Introduction
+
+As the mobile Internet rushes in, a variety of video live streaming applications begin to emerge. In addition, online live shopping, online live education and other real-time communication multimedia applications, which are known as interactive live streaming applications, have become popular. The "interactivity" brings another practical requirement of live streaming business. Different from the one-way transmission of traditional media streams, interactive live streaming applications require new two-way channels to meet interactive requirements. Traditional live video systems over the Internet usually utilize content delivery network (CDN) for video distribution. The mainstream protocols adopted include real time messaging protocol (RTMP), hypertext transfer protocol (HTTP)/FLV, HTTP live streaming (HLS), etc., and there have been numerous diversified optimizations for traditional live broadcasting application scenarios. However, CDN adopts a tree-like hierarchical structure (which can be referenced from [b-ITU-T H.644.3]) and uses transmission control protocol (TCP) protocol for video transmission. Consequently, it is desirable to significantly reduce the end-to-end transmission delay.
+
+A two-way low-latency multimedia delivery system over the Internet is required to satisfy the above requirements. In this Recommendation, an interactive low-latency multimedia transmission system (ILMTS) over the Internet is introduced. The ILMTS has many interactive network audio/video-based application scenarios, such as e-commerce live broadcasting, online multi-party meeting, live distance learning, video chat and cloud games.
+
+Figure 6-1 presents an overview of ILMTS deployment.
+
+
+
+The diagram shows the ILMTS architecture. At the top, a 'Control centre' (three server icons) is connected to a central 'Bi-direction delivery network' (cloud with five 'Relay' nodes). Below the control centre, two zones, 'Zone A' and 'Zone B', are shown. Each zone contains an 'Access point' (tower icon) connected to multiple 'Client' devices (laptop, monitor, smartphone icons). The 'Access point' in Zone A is connected to the 'Bi-direction delivery network' via a 'Relay' node, and similarly for Zone B. The 'Bi-direction delivery network' is connected to the 'Internet' (cloud with nodes) via an 'Overlay' connection. The entire ILMTS structure is enclosed in a dashed box labeled 'ILMTS'.
+
+Figure 6-1: Example of ILMTS over Internet. The diagram illustrates the ILMTS architecture. At the top, a 'Control centre' (represented by three server icons) is connected to a central 'Bi-direction delivery network' (a cloud containing five 'Relay' nodes). Below the control centre, two zones, 'Zone A' and 'Zone B', are shown. Each zone contains an 'Access point' (represented by a tower icon) which is connected to multiple 'Client' devices (represented by icons of a laptop, monitor, and smartphone). The 'Access point' in Zone A is connected to the 'Bi-direction delivery network' via a 'Relay' node, and similarly for Zone B. The 'Bi-direction delivery network' is connected to the 'Internet' (represented by a cloud containing several nodes) via an 'Overlay' connection. The entire ILMTS structure is enclosed in a dashed box labeled 'ILMTS'.
+
+F.746.18(24)
+
+**Figure 6-1 – Example of ILMTS over Internet**
+
+ILMTS adopts a hybrid network structure that combines the hierarchy and peer-to-peer (P2P) networking modes. Meanwhile, the multiple efficient video transmission technologies can be used for optimizing the end-to-end performance of video delivery, including dynamic P2P routing planning, low-latency content transport protocol and distributed edge content processing. Through
+
+elaborate design and fine-tuning of the delivery mechanism, ILMTS can achieve an end-to-end transmission delay of hundreds of milliseconds.
+
+# **7 Requirements for interactive low-latency multimedia transmission system over the Internet**
+
+### **7.1 Service requirements**
+
+[SR-01]: ILMTS is recommended to support the convergence of cloud and network technologies, which means that ILMTS can be composed of overlay network (cloud) and infrastructure network (network).
+
+[SR-02]: The server-side functions of ILMTS, specifically the control, relay and access functions outlined in this Recommendation, are recommended to be deployed in an overlay network utilizing a cloud-based approach.
+
+[SR-03]: ILMTS is recommended to support the collaboration of cloud-edge-client, that is, the functional components of ILMTS can be deployed in the different areas of network and are capable of working collaboratively by interaction of control signalling and interaction of media transmission.
+
+[SR-04]: ILMTS is recommended to support the layered architecture by the separation of data plane and control plane.
+
+## **7.2 Management requirements**
+
+[MGR-01]: The control plane of ILMTS is recommended to be deployed in the central cloud, as a control centre.
+
+[MGR-02]: The control plane of ILMTS is recommended to support the management and programming of access point and relay node, which includes access scheduling and routing scheduling.
+
+[MGR-03]: Access scheduling is recommended to support the following aspects, but not limited to:
+
+- Support data aggregation: to be capable of collecting the information of access point, the network information detected between client and access point.
+- Support maintenance of static/dynamic IP address database: to be capable of filtering the aggregated data and categorizing the data according to the position of the access point.
+- Support intelligent allocation of access point: to be capable of selecting the optimal access point according to the parameter of service request and pre-processed data.
+- Support query of candidate access point: to be capable of providing the most appropriate access point to the client.
+
+[MGR-04]: The routing scheduling is recommended to support the following aspects, but not limited to:
+
+- Support data aggregation: to be capable of collecting the information of the relay node, the network information detected within relay nodes.
+- Support data pre-process: to be capable of filtering the aggregated data and categorizing the data according to the different conditions.
+- Support intelligent routing among the relay nodes: to be capable of computing optimal network routing and dynamically generating of quantified network topology, according to the pre-processed data.
+- Support query of routing information: to be capable of providing the customized query of routing between relay nodes.
+
+### 7.3 Accounting requirements
+
+[AR-01]: ILMTS is recommended to support the diversified billing models based on the accounting factors such as duration, traffic and capacity types.
+
+[AR-02]: The billing model can optionally be divided into different levels and package rates. For example, it can be billed according to monthly/annual subscription, license, service level agreement (SLA), etc.
+
+### 7.4 Networking requirements
+
+[NTR-01]: ILMTS is recommended to deploy multiple relay nodes and access points for a high-quality and high-reliability media transmission network.
+
+[NTR-02]: The networking of ILMTS relay nodes and access points is recommended to be harmonized with the network architecture of infrastructure transport network.
+
+[NTR-03]: The access point of ILMTS is recommended to be deployed in the edge network, as the geographic location closest to the end-user. It is recommended to support the following aspects, but not limited to:
+
+- It composes of multiple light-weight nodes and covers all areas within ILMTS.
+- It is capable of transmitting the detection information of client accessing and the information of access point itself to the control centre.
+- It is capable of high-reliability and high-stability accessing.
+
+[NTR-04]: The Relay node of ILMTS is recommended to be deployed in the backbone network, as the data relaying between different zones. It is recommended to support the following aspects, but not limited to:
+
+- It is a large-scaled node composed of high-performance servers and a large quantity of storage.
+- It supports multipoint-to-multipoint network connection.
+- It is capable of transmitting the network detection information among the relay nodes and the information of relay node itself to the control centre.
+- It is capable of high-speed and high-quality data forwarding.
+
+### 7.5 Quality of Service (QoS) and performance requirements
+
+[QPR-01]: ILMTS can optionally support the QoS guaranteed by collaboration of overlay network layer (cloud) and infrastructure network layer (network).
+
+### 7.6 Scalability requirements
+
+[SCR-01]: ILMTS is recommended to run its system resource on container cloud and microservice architecture, which is based on a cloud-based infrastructure.
+
+[SCR-02]: The server hardware resource of ILMTS is recommended to be cloudified so that it is able to construct a cloud-based infrastructure like platform as a service (PaaS).
+
+[SCR-03]: The system resource of ILMTS is recommended to support the flexible resource scaling. The scaling strategy can be:
+
+- Adjust the quantity of running instance dynamically based on the scale of service capability.
+- Configure the strategy of scaling and threshold for each specific system element, based on the monitoring of the related element resource occupancy status, such as the central processing unit (CPU)/memory occupancy rate.
+- Periodical resource scalability.
+
+[SCR-04]: ILMTS can optionally adopt the docker model to reduce the wastage of conventional virtual machine (VM) resources.
+
+# 8 Reference framework
+
+The entire ILMTS consists of four parts: Control centre, relay node, access points (also called edge node) and client. To provide a low-latency interactive media delivery, a dynamic media delivery path optimization mechanism is required to be applied and it relies on the collaboration of all components of ILMTS.
+
+Figure 8-1 presents the high-level framework of ILMTS.
+
+
+
+The diagram illustrates the high-level framework of ILMTS, organized into four stacked layers. The top layer, 'Control centre', is grouped under the label 'Control plane' and contains three modules: 'Network awareness', 'Path planning', and 'Scheduling management'. The subsequent three layers are grouped under the label 'Data plane'. These are: 'Relay node' (containing 'Data forwarding', 'Data receiving', 'Path management', and 'Forwarding detection'), 'Access point (Edge node)' (containing 'Data forwarding', 'Data receiving', 'Path management', and 'Access detection'), and 'End-user (Client)' (containing 'Data generation', 'Content processing', 'Path management', and 'Client detection'). A small code 'F.746.18(24)' is visible at the bottom right of the diagram.
+
+Figure 8-1 – Reference framework diagram showing the four layers of ILMTS: Control centre, Relay node, Access point (Edge node), and End-user (Client). The Control centre is part of the Control plane, while the other three are part of the Data plane.
+
+**Figure 8-1 – Reference framework**
+
+### – Control centre
+
+The control centre is responsible for the management of diverse data. It controls the relay node and access point for data forwarding and routing path planning. The control centre is capable of network performance awareness and performs global routing path management and scheduling. Typically, network status and the running status of the relay node, access point and client should be processed in the control centre, as the basis of routing path planning.
+
+### – Relay node
+
+The relay node can be regarded as the application-layer data forwarding router, capable of forwarding data with high-speed and high-quality among relay nodes. It is further composed of modules for forwarding detection, data forwarding, data receiving and path management.
+
+### – Access point
+
+Access point, also called edge node, is responsible for connecting the client to the ILMTS with high-reliability and high-stability. The access point can be further composed of access detection, path management, data receiving and data forwarding modules.
+
+### – Client (end-user/terminal device)
+
+The client consists of a variety of physical devices or software applications that support the generation, transmission and display of media data. For example, in video conferencing services, the client may include PC clients, mobile phone clients, and conference terminals in conference rooms. In cloud computing services, it could encompass thin terminals, PC, back-end servers, etc. For extended reality (XR) services, it may include glasses terminals, head-mounted terminals and back-end servers. The client can be further subdivided into modules of client detection, path management, content processing, data forwarding.
+
+## Appendix I
+
+### Use cases for interactive low-latency multimedia transmission system over the Internet
+
+(This appendix does not form an integral part of this Recommendation.)
+
+### I.1 E-commerce live broadcasting
+
+E-commerce live broadcast refers to an enhanced application of live video broadcast. It adds interactive functions in live video broadcast, including large concurrent live broadcast oriented to users and two-way video interaction with viewers. Interactive enabled live broadcast can establish a low-latency video interaction between the main broadcast and viewers at any time. It has made essential changes in viewing experience and presentation effects and represents the development trend of live video broadcast applications. E-commerce live broadcast, online interactive education, and other popular forms on the network are typical application scenarios of interactive live broadcast.
+
+### I.2 Multiparty visual meeting
+
+A multiparty visual meeting refers to a simulated face-to-face conference between two or more individuals or groups in different places through a low-latency video/audio transport system and multimedia devices. Video conferencing is a kind of real-time telepresence, where in addition to seeing the caller and verbal communication, the person's expression and actions can be seen, making people in different places communicate as if they were in the same room.
+
+### I.3 Live distance learning
+
+Live distance learning refers to an education mode provided without the teacher and students being physically present in the same place. The traditional education mode usually offers correspondence courses materials sent to a student by paper or mail, and assignments were completed online or returned to the teacher by mail. The live distance learning programs can provide the opportunities for the students to obtain the online course materials while they are involving in a real-time online class. They can also use interactive tools, such as a virtual white board, to discuss with other classmates and complete the online assignments within a limited time.
+
+### I.4 Video chat
+
+A video chat is a phone call that uses an Internet connection, sometimes called voice over internet protocol (VoIP), which utilizes video to transmit a live picture of the person making the call. Video chats are made using a computer's webcam or other electronic hardware devices with a video-capable camera, like a smartphone, tablet or video-capable phone system. In some cases, video calling can also provide interactive elements such as live white board (similar to the video conference) while two or more users are still in a video call.
+
+### I.5 Cloud games
+
+A cloud game (cloud gaming), which may also be referred to as game on demand (gaming on demand), is an online game technology based on a cloud computing technology. Cloud gaming technology enables light-end devices (thin client) with relatively limited graphics and data computing capabilities to a run high-quality game. In a cloud gaming scenario, the game is not performed on a player's game terminal, but runs on a cloud server. The cloud server renders the game scenario into a video and audio stream and transmits the video and audio stream to the player's game terminal over an ultra-low latency network. Gamers do not need to have powerful graphic computing and data processing capabilities, but only need to have basic streaming media playback capabilities and the capability of getting instructions from gamers and sending them to the cloud server.
+
+### **I.6 Cloud computer**
+
+A cloud computer, also called a cloud desktop, is a new model that replaces traditional computers. Compared with a traditional computer, a cloud computer does not have hardware such as a CPU, memory and a hard disk. All the hardware is integrated in a data centre in the cloud. Users can access their personal desktop, data and applications from a single, compact client device that can be connected anywhere where there is a network, connecting to a keyboard, mouse and monitor the same way as with an ordinary personal computer. The user's operation and the operation results should be reflected in a very short time between user and the data centre in the cloud. Therefore, the control signal and the media steam should be transmitted relied on an interactive low-latency media transport system.
+
+### **I.7 Cloud rendering**
+
+Cloud rendering means that a 3D program is rendered on a remote server. A user client uses web software or a local 3D program to click a "cloud rendering" button and access resources through an interactive low-latency Internet access. An instruction is sent from the user client, and the server executes the corresponding rendering task according to the instruction. A rendering result image is sent back to the user client for display.
+
+## Bibliography
+
+- [b-ITU-T F.747.13] Recommendation ITU-T F.747.13 (2023), *Requirements and reference framework of cloud-edge collaboration in industrial machine vision systems.*
+- [b-ITU-T H.644.3] Recommendation ITU-T H.644.3 (2020), *Functional architecture of multimedia content delivery networks.*
+- [b-ITU-T J.1301] Recommendation ITU-T J.1301 (2021), *Specification of cloud-based converged media service to support Internet protocol and broadcast cable television – Requirements.*
+- [b-ITU-T J.1305] Recommendation J.1305 (2023), *Requirements for microservices architecture for audiovisual media in the converged media cloud.*
+- [b-ITU-T Y.2011] Recommendation ITU-T Y.2011 (2004), *General principles and general reference model for Next Generation Networks.*
+- [b-ITU-T Y.3535] Recommendation ITU-T Y.3535 (2022), *Cloud computing – Functional requirements for a container.*
+- [b-ISO/IEC TS 23167] Technical Specification ISO/IEC TS 23167:2020, *Information technology – Cloud computing – Common technologies and techniques.*
+
+
+
+
+
+## SERIES OF ITU-T RECOMMENDATIONS
+
+| | |
+|-----------------|-----------------------------------------------------------------------------------------------------------------------------------------------------------|
+| Series A | Organization of the work of ITU-T |
+| Series D | Tariff and accounting principles and international telecommunication/ICT economic and policy issues |
+| Series E | Overall network operation, telephone service, service operation and human factors |
+| Series F | Non-telephone telecommunication services |
+| Series G | Transmission systems and media, digital systems and networks |
+| Series H | Audiovisual and multimedia systems |
+| Series I | Integrated services digital network |
+| Series J | Cable networks and transmission of television, sound programme and other multimedia signals |
+| Series K | Protection against interference |
+| Series L | Environment and ICTs, climate change, e-waste, energy efficiency; construction, installation and protection of cables and other elements of outside plant |
+| Series M | Telecommunication management, including TMN and network maintenance |
+| Series N | Maintenance: international sound programme and television transmission circuits |
+| Series O | Specifications of measuring equipment |
+| Series P | Telephone transmission quality, telephone installations, local line networks |
+| Series Q | Switching and signalling, and associated measurements and tests |
+| Series R | Telegraph transmission |
+| Series S | Telegraph services terminal equipment |
+| Series T | Terminals for telematic services |
+| Series U | Telegraph switching |
+| Series V | Data communication over the telephone network |
+| Series X | Data networks, open system communications and security |
+| Series Y | Global information infrastructure, Internet protocol aspects, next-generation networks, Internet of Things and smart cities |
+| Series Z | Languages and general software aspects for telecommunication systems |
\ No newline at end of file
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+
+
+**ITU-T**
+
+TELECOMMUNICATION
+STANDARDIZATION SECTOR
+OF ITU
+
+**F.746.2**
+
+(02/2014)
+
+SERIES F: NON-TELEPHONE TELECOMMUNICATION
+SERVICES
+
+Audiovisual services
+
+---
+
+**Service description for user data exchange
+between functional components in network
+entities and terminals**
+
+Recommendation ITU-T F.746.2
+
+# ITU-T F-SERIES RECOMMENDATIONS **NON-TELEPHONE TELECOMMUNICATION SERVICES**
+
+| | |
+|-----------------------------------------------------------------|--------------------|
+| TELEGRAPH SERVICE | |
+| Operating methods for the international public telegram service | F.1–F.19 |
+| The gentex network | F.20–F.29 |
+| Message switching | F.30–F.39 |
+| The international telemessage service | F.40–F.58 |
+| The international telex service | F.59–F.89 |
+| Statistics and publications on international telegraph services | F.90–F.99 |
+| Scheduled and leased communication services | F.100–F.104 |
+| Phototelegraph service | F.105–F.109 |
+| MOBILE SERVICE | |
+| Mobile services and multdestination satellite services | F.110–F.159 |
+| TELEMATIC SERVICES | |
+| Public facsimile service | F.160–F.199 |
+| Teletex service | F.200–F.299 |
+| Videotex service | F.300–F.349 |
+| General provisions for telematic services | F.350–F.399 |
+| MESSAGE HANDLING SERVICES | F.400–F.499 |
+| DIRECTORY SERVICES | F.500–F.549 |
+| DOCUMENT COMMUNICATION | |
+| Document communication | F.550–F.579 |
+| Programming communication interfaces | F.580–F.599 |
+| DATA TRANSMISSION SERVICES | F.600–F.699 |
+| AUDIOVISUAL SERVICES | F.700–F.799 |
+| ISDN SERVICES | F.800–F.849 |
+| UNIVERSAL PERSONAL TELECOMMUNICATION | F.850–F.899 |
+| HUMAN FACTORS | F.900–F.999 |
+
+*For further details, please refer to the list of ITU-T Recommendations.*
+
+# Recommendation ITU-T F.746.2
+
+# Service description for user data exchange between functional components in network entities and terminals
+
+## Summary
+
+Recommendation ITU-T F.746.2 describes user data exchange scenarios and a basic approach of exchanging user data between terminals or between terminals and network entities by using data packages encapsulating formatted user data. The functionality of the components which implement the data exchange and general guidance of generating and parsing such data package are given as well. This Recommendation also describes the preferred extensible markup language (XML) representations used when encapsulating corresponding user data, including, but not limited to, contacts, messages and other user data categories.
+
+## History
+
+| Edition | Recommendation | Approval | Study Group | Unique ID* |
+|---------|----------------|------------|-------------|---------------------------------------------------------------------------|
+| 1.0 | ITU-T F.746.2 | 2014-02-13 | 16 | 11.1002/1000/12050 |
+
+## Keywords
+
+Data exchanging agent (DXA), user data exchange, XML.
+
+---
+
+\* To access the Recommendation, type the URL in the address field of your web browser, followed by the Recommendation's unique ID. For example, .
+
+## FOREWORD
+
+The International Telecommunication Union (ITU) is the United Nations specialized agency in the field of telecommunications, information and communication technologies (ICTs). The ITU Telecommunication Standardization Sector (ITU-T) is a permanent organ of ITU. ITU-T is responsible for studying technical, operating and tariff questions and issuing Recommendations on them with a view to standardizing telecommunications on a worldwide basis.
+
+The World Telecommunication Standardization Assembly (WTSA), which meets every four years, establishes the topics for study by the ITU-T study groups which, in turn, produce Recommendations on these topics.
+
+The approval of ITU-T Recommendations is covered by the procedure laid down in WTSA Resolution 1.
+
+In some areas of information technology which fall within ITU-T's purview, the necessary standards are prepared on a collaborative basis with ISO and IEC.
+
+## NOTE
+
+In this Recommendation, the expression "Administration" is used for conciseness to indicate both a telecommunication administration and a recognized operating agency.
+
+Compliance with this Recommendation is voluntary. However, the Recommendation may contain certain mandatory provisions (to ensure, e.g., interoperability or applicability) and compliance with the Recommendation is achieved when all of these mandatory provisions are met. The words "shall" or some other obligatory language such as "must" and the negative equivalents are used to express requirements. The use of such words does not suggest that compliance with the Recommendation is required of any party.
+
+## INTELLECTUAL PROPERTY RIGHTS
+
+ITU draws attention to the possibility that the practice or implementation of this Recommendation may involve the use of a claimed Intellectual Property Right. ITU takes no position concerning the evidence, validity or applicability of claimed Intellectual Property Rights, whether asserted by ITU members or others outside of the Recommendation development process.
+
+As of the date of approval of this Recommendation, ITU had not received notice of intellectual property, protected by patents, which may be required to implement this Recommendation. However, implementers are cautioned that this may not represent the latest information and are therefore strongly urged to consult the TSB patent database at .
+
+© ITU 2014
+
+All rights reserved. No part of this publication may be reproduced, by any means whatsoever, without the prior written permission of ITU.
+
+## Table of Contents
+
+| | Page |
+|--------------------------------------------------------------|------|
+| 1 Scope..... | 1 |
+| 2 References..... | 1 |
+| 3 Definitions ..... | 2 |
+| 3.1 Terms defined elsewhere ..... | 2 |
+| 3.2 Terms defined in this Recommendation..... | 2 |
+| 4 Abbreviations and acronyms ..... | 2 |
+| 5 Conventions ..... | 3 |
+| 6 General..... | 3 |
+| 7 Scenarios of user data exchange ..... | 3 |
+| 7.1 User data grouping ..... | 3 |
+| 7.2 Scenario description ..... | 4 |
+| 8 User data exchange method ..... | 4 |
+| 8.1 General procedure ..... | 4 |
+| 8.2 Data package ..... | 5 |
+| 9 Functionality of data exchange functional components ..... | 6 |
+| 9.1 Basic functionality ..... | 6 |
+| 9.2 Security consideration ..... | 6 |
+| 10 Preferred XML user data syntax..... | 7 |
+| 10.1 General ..... | 7 |
+| 10.2 Contacts data syntax ..... | 7 |
+| 10.3 Calendar data syntax..... | 7 |
+| 10.4 Messaging data syntax..... | 7 |
+| 10.5 Other ..... | 10 |
+
+
+
+# Service description for user data exchange between functional components in network entities and terminals
+
+# 1 Scope
+
+The general purpose of this Recommendation is to describe user data exchange scenarios and a basic approach to exchange user data between terminals or between terminals and network entities by using data packages encapsulating formatted user data. The functionality of the components which implement the data exchange and general guidance of generating and parsing such data packages are given as well. This Recommendation also describes the preferred extensible markup language (XML) representations used when encapsulating corresponding user data, including, but not limited, to contacts, messages and other user data categories.
+
+This Recommendation applies to terminals and network entities which choose to implement user data exchanging functions as described in this Recommendation.
+
+# 2 References
+
+The following ITU-T Recommendations and other references contain provisions which, through reference in this text, constitute provisions of this Recommendation. At the time of publication, the editions indicated were valid. All Recommendations and other references are subject to revision; users of this Recommendation are therefore encouraged to investigate the possibility of applying the most recent edition of the Recommendations and other references listed below. A list of the currently valid ITU-T Recommendations is regularly published. The reference to a document within this Recommendation does not give it, as a stand-alone document, the status of a Recommendation.
+
+- [ETSI TS 123 140] ETSI TS 123 140 V6.16.0 (2009), *Digital cellular telecommunications system (Phase 2+); Universal Mobile Telecommunications System (UMTS); Multimedia Messaging Service (MMS); Functional description; Stage 2* (3GPP TS 23.140 version 6.16.0 Release 6).
+- [ETSI TS 126 140] ETSI TS 126 140 V7.1.0 (2007), *Digital cellular telecommunications system (Phase 2+); Universal Mobile Telecommunications System (UMTS); Multimedia Messaging Service (MMS); Media formats and codes* (3GPP TS 26.140 version 7.1.0 Release 7).
+- [ETSI TS 127 005] ETSI TS 127 005 V3.2.0 (2002), *Digital cellular telecommunications system (Phase 2+); Universal Mobile Telecommunications System (UMTS); Use of Data Terminal Equipment – Data Circuit terminating Equipment (DTE – DCE) interface for Short Message Service (SMS) and Cell Broadcast Service (CBS)* (3GPP TS 27.005 version 3.2.0 Release 1999).
+- [IETF RFC 5545] IETF RFC 5545 (2009), *Internet Calendaring and Scheduling Core Object Specification (iCalendar)*.
+- [IETF RFC 6321] IETF RFC 6321 (2011), *xCal: The XML Format for iCalendar*.
+- [IETF RFC 6350] IETF RFC 6350 (2011), *vCard Format Specification*.
+- [IETF RFC 6351] IETF RFC 6351 (2011), *xCard: vCard XML Representation*.
+- [W3C XML] W3C XML 1.0 (2008), *Extensible Markup Language (XML) 1.0 (Fifth Edition)*.
+- [W3C XMLEnc] W3C XML Encryption (2002), *XML Encryption Syntax and Processing*.
+
+# 3 Definitions
+
+## 3.1 Terms defined elsewhere
+
+None.
+
+## 3.2 Terms defined in this Recommendation
+
+This Recommendation defines the following terms:
+
+**3.2.1 data exchanging agent:** Logic in terminals or entities where the main function is to put data into or extract data from the data package described in this Recommendation. Furthermore, it monitors the data exchange process and takes actions when specific user data is encountered after the data exchange process. A typical form of the functional component is an extensible markup language (XML) parser combined with application-dependent logic.
+
+**3.2.2 depository:** A depository is a location where the user data could be stored or kept so that it could be accessed later. It can take various forms such as internal or external memory of terminals, network storage servers and other storage devices.
+
+**3.2.3 user data:** "User data" is the data that is created or stored in terminals or network entities by the users, and is related to the private information, historical operations performed by the user, personal tendencies or favourite user settings. It is independent of whether this data is transported by terminal or network entities, and has no correlation with the counterpart of "Control data".
+
+# 4 Abbreviations and acronyms
+
+This Recommendation uses the following abbreviations and acronyms:
+
+| | |
+|------|-------------------------------|
+| DRM | Digital Rights Management |
+| DXA | Data exchanging Agent |
+| FTP | File Transfer Protocol |
+| HTTP | Hypertext Transfer Protocol |
+| IM | Instant Message |
+| MMS | Multimedia Message Service |
+| RAM | Random Access Memory |
+| ROM | Read Only Memory |
+| SD | Secure Digital |
+| SIM | Subscriber Identity Module |
+| SMS | Short Message Service |
+| URL | Uniform Resource Locator |
+| USB | Universal Serial Bus |
+| USIM | User Services Identity Module |
+| W3C | World Wide Web Consortium |
+| XML | Extensible Markup Language |
+
+# 5 Conventions
+
+None.
+
+# 6 General
+
+Under many circumstances there is a need to exchange user data between terminals or network entities and another data depository. For example, a user may want to replace a terminal with a new terminal without losing personal data, such as contacts and received messages, stored in the original one. The data exchange process might be initiated by the user manually or by a network application automatically, and multiple categories of data might be involved in an exchange process. However, the terminals or entities acting as the source and destination in the exchange process may use different operating systems or different internal data expressions for the same kind of data. Without a consistent approach, accurate exchange of the user data is difficult to realize.
+
+To facilitate the exchange process and make it as simple as possible for the users, this Recommendation describes an exchange approach by using a data package as a container to encapsulate user data and specifies the recommended data syntax for parsing or generating the data package.
+
+# 7 Scenarios of user data exchange
+
+## 7.1 User data grouping
+
+The user data includes the user's personal data, device configuration parameters and personalized application data, and can be stored in terminals or other entities, no matter the device type. User data may take various forms such as binary, text or multimedia files depending on the corresponding data category. It could be stored in different locations such as internal memory (RAM, ROM, etc.) and external memory (SIM/USIM, SD card, hard disk, etc.).
+
+### 7.1.1 Private user data
+
+Private user data is created by the user for a special purpose or generated by the users operations and contains important information about the user. Examples of private user data include:
+
+- Contact information (including phonebook)
+- Messages (including SMS, MMS, IM and e-mail)
+- Calendar information
+- Favourite uniform resource locator (URL) lists and bookmarks
+- Call and browsing history
+
+### 7.1.2 Device configuration data
+
+Device configuration data is the data that a terminal allows users to access and modify, so as to personalize what the terminal displays and the way it behaves. Examples of device configuration data include:
+
+- Terminal theme, fonts, wallpaper and screensaver
+- Language settings
+- Date/Time and location settings
+- Energy saving settings
+- Accessibility settings
+
+### 7.1.3 Personalized application data
+
+Personalized application data is the data that applications allow users to access and modify, so as to personalize the way an application operates or behaves, including:
+
+- Service dependent settings or parameters
+- Application settings or application files
+
+## 7.2 Scenario description
+
+A basic user data exchange scenario is that a terminal or an entity wants to receive discrete sets of user data from another terminal or to send data to another terminal. For example, a mobile phone desires to retrieve all the contacts and calendar data stored in another terminal. Another example would be that an entity in the network needs to receive a status report or needs to retrieve the browsing history of the streaming media player on the terminal to use for later statistical purposes.
+
+In those cases, typically user data is of small size and may be stored in different formats in the two terminals because of different operating platforms or different data management applications. To exchange data, normally the data providing party will generate a data package which contains multiple categories of data, and the other party receives the data package and performs data analysis, followed by certain operations according to the original purpose of this data acquisition process.
+
+# 8 User data exchange method
+
+## 8.1 General procedure
+
+For a typical user data exchange scenario, the data exchange process can be summarized into several steps: Export, transfer and analyse.
+
+- Export: Export selected user data from party A as an accessible data package.
+- Transfer: Party A transfers the selected package to party B by any approach. This step does not need to be in real time.
+- Analyse: Party B opens the package and performs the analysis. It retrieves all the needed data or supported data according to the pre-defined data format or expression. This is followed by certain operations based on the retrieved data.
+
+The data package which contains all the user data forms the basis of data exchange. To ensure compatibility, the data package is defined in an extensible markup language (XML) format as specified in [W3C XML] so that it may be supported and applied in various applications across different operating systems and terminals. Furthermore, the data package is able to encapsulate multiple categories of data and is also extendable to new data categories. This Recommendation uses XML for the user data in the data package as it is designed to describe structured data, is naturally extendable and widely supported by many applications and operating systems.
+
+The transfer step encompasses transferring a data package between a terminal and another entity. There are various techniques for transferring files (such as the XML data package files), including file transfer protocol (FTP), hypertext transfer protocol (HTTP), Bluetooth and infrared via short ranged wireless communication and universal serial bus (USB) storage via wired connections. The transfer may be real-time or may be a store and forward arrangement. There may be extra processing during the data package transfer. The data package may also be moved to another depository and accessed at a later time as necessary.
+
+The export and analyse steps could be implemented by functional components. These components are deployed in the terminals or the entities acting as data exchange agents to manage the data exchange. The data exchange process is illustrated in Figure 1.
+
+
+
+Figure 1 – Data exchange procedure diagram. The diagram shows two 'Terminal or entities' boxes, each enclosed in a dashed rectangle. The left box contains 'Required data' pointing to a 'DXA (Export)' box, which points to a 'Data package' (represented by a document icon). A dashed arrow labeled 'Transferring or processing' connects the first 'Data package' to a second 'Data package'. The second 'Data package' points to a 'DXA (Analyse)' box, which points to 'Retrieved data' inside the right 'Terminal or entities' box. The text 'F.746.2(14)\_F01' is at the bottom right.
+
+**Figure 1 – Data exchange procedure**
+
+## 8.2 Data package
+
+### 8.2.1 Example
+
+The data package is an XML encoded structure. A simple example of a data package containing the contacts information, calendar records and instant message history, which is used for exchanging private user data between two terminals, is illustrated as follows:
+
+```
+
+
+ 1.0
+ 0
+
+ 2010-08-10T14:30:00Z
+ MobilePhone_Vendor_X
+ TypeNumber_2321C
+ Data_export_Manager
+
+
+
+
+
+
+
+
+
+
+
+
+
+```
+
+### 8.2.2 element
+
+The root element in this XML structure is which is also the beginning of the XML structure. When packing data into the element, the format should follow the XML schema 1.1 description of the element, which follows [W3C XSD], as listed below:
+
+```
+
+
+
+
+
+
+
+
+
+
+
+
+```
+
+```
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+```
+
+In the element, there are several child elements:
+
+- : this element indicates the version of this XML file.
+- : this element indicates the encryption status of this XML file.
+- : this element contains the following descriptive information about the data package:
+ - : Contains a string indicating the creation time of this package according to the format
+ - : Contains a string indicating information about the terminal vendor.
+ - : Contains a string indicating information about the terminal itself.
+ - : Contains a string indicating information about the application generating the data package.
+- : this element contains the main body of the data to be exchanged.
+
+### 8.2.3 element
+
+The is the main element which contains the data to be exchanged. Any XML formulated user data that follows the corresponding XML representations defined in the existing specifications or defined by applications itself may be stored in this element.
+
+# 9 Functionality of data exchange functional components
+
+## 9.1 Basic functionality
+
+The data exchanging agent (DXA) should be able to generate and parse the XML data package. When parsing the XML data package, the DXA should ignore unsupported data in the data package without interrupting the data exchange process or generating an unexpected exception error.
+
+The DXA should be capable of supporting the updating of the data set definition. This functionality may be realized by updating the corresponding XML definition of the supported data.
+
+The DXA should, when appropriate, avoid data collision when storing the retrieved data from the exchange process, possibly by noting the existing user data records. When data collision might occur, actions such as prompts to user or user data merging according to predefined rules should be taken.
+
+## 9.2 Security consideration
+
+The decision to take action to ensure the security of user data exchange depends on the application implementation and the data sensitivity. For some real-time implementations of user data exchange, security issues could be addressed in the transport layer by secure file transfer. For other non-real-
+
+time implementations, for example where the generated data package would be temporarily stored in public websites, simple password protection or XML encryption according to [W3C XMLEnc] may be applied on the data package to prevent unauthorized access of the user data.
+
+When XML encryption is used to create the data package, the DXA should be capable of encrypting the user data and decrypting the XML encrypted data according to the [W3C XMLEnc].
+
+# 10 Preferred XML user data syntax
+
+## 10.1 General
+
+Whether the data retrieved from the data package can be successfully understood will depend on the XML user data syntax. If the XML user data syntax in the data package perfectly matches the internal storage format used by the terminal or the entities which receive the data package, then the user data exchange can be performed without any compatibility problem, otherwise the exchange process may suffer data loss.
+
+User data typically has its own distinctive format, which may be different between multiple terminals and/or operating systems. Moreover some kinds of user data do not use popular or globally-accepted formats. This Recommendation defines XML syntax for several common forms of user data in order to improve interoperability between the entities.
+
+## 10.2 Contacts data syntax
+
+For representing and exchanging contact and relevant information about individuals and other entities, IETF has specified vCard data format in [IETF RFC 6350], which is a text-based format.
+
+The XML representation for vCard is defined by [IETF RFC 6351]. The underlying data structure is exactly the same as the original vCard text format, which supplies the one-to-one mapping between the original vCard format and the XML representation.
+
+The contacts XML representation should follow the vCard XML format, which is specified in [IETF RFC 6351].
+
+## 10.3 Calendar data syntax
+
+For the calendaring and scheduling data, IETF has defined the iCalendar data format in [IETF RFC 5545]. The iCalendar data format is a widely deployed interchange format. While many applications and services on the Internet support and generate calendar data, similar to the vCard format, an iCalendar XML representation has been defined. This supplies a one-to-one mapping between the original iCalendar format and the XML representation.
+
+The calendaring XML representation should follow the iCalendar XML formats, which is specified in [IETF RFC 6321].
+
+## 10.4 Messaging data syntax
+
+### 10.4.1 SMS syntax
+
+For exchanging the SMS data stored in mobile terminals or other storages, the recommended XML schema representation following XML schema 1.1 is shown as below:
+
+```
+
+
+
+
+
+
+
+
+
+```
+
+```
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+```
+
+When converting SMS data to XML representation, the SMS information data fields should be mapped to XML elements correctly. The specific data format and meaning for each element is described as below:
+
+ is the root element for storing SMS. It may contain multiple elements.
+
+ is the element containing data for one SMS record, it has several fields:
+
+- : Contains a string with the address information of the terminals or the entities sending the SMS, the specific format shall follow the address definition of SMS in [ETSI TS 127 005].
+- : Contains a string with the address information of the recipient of the SMS, the specific format shall follow the address definition of SMS in [ETSI TS 127 005].
+- : Contains a string with the text content of the SMS, the format of the string shall follow the short message data format definition in [ETSI TS 127 005].
+- : Contains a string indicating the creating time of this SMS record when it is received, sent out or generated within the terminal or the entities, the format of the time shall follow the time string format defined in [ETSI TS 127 005].
+- : this is the elements indicating the status of the SMS:
+ - : If the SMS is sent to the terminals or the entities by other terminals or entities, this field shall be set to 1; otherwise it shall be set to 0.
+ - : If the SMS is sent out by the terminals or the entities to other terminals or entities, this field shall be set to 1; otherwise it shall be set to 0.
+ - : If the SMS is generated within the terminals or the entities and hasn't been sent out, this field shall be set to 1; otherwise it shall be set to 0.
+ - : If the SMS is a delivery report from the SMS service centre located in the network, this field shall be set to 1; otherwise it shall be set to 0.
+- : Contains a string about any extra descriptive information of the SMS if supported by the terminals or the entities.
+
+### 10.4.2 MMS Syntax
+
+For exchanging the multimedia message service (MMS) data stored in the mobile terminals or other storages, the recommended XML schema representation following XML schema 1.1 is shown as below:
+
+```
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+```
+
+When converting MMS data to XML representation, the MMS information data fields should be mapped to the XML elements correctly, the specific data format and the meaning for each MMS information field is described below:
+
+ is the root element for storing MMS. It may contain multiple elements.
+
+ is the element containing data for one MMS record, it has several fields:
+
+- : Contains several fields holding the content of the MMS.
+
+- : Contains a string indicating the character encoding for text as specified in [ETSI TS 126 140].
+- : Contains a string indicating the content encoding type as specified in [ETSI TS 123 140].
+- : Contains a string with the reference location of MMS content as specified in [ETSI TS 123 140].
+- : Contains a string with the encoded data of the MMS.
+- : Contains a string with the indicator of content type as defined in [ETSI TS 123 140].
+- : Contains several fields of more descriptive information.
+ - : Contains a string with the descriptive information of the nature of the content, such as indications of the classified contents of the MMS and the digital rights management (DRM) status, as defined in [ETSI TS 123 140].
+ - : Contains a string with the media type and formats of the classified content as defined in [ETSI TS 123 140].
+ - : Contains a string about the index of the MMS as defined in [ETSI TS 123 140].
+- : Contains a string with the message type of MMS, as defined in [ETSI TS 123 140].
+- : Contains a string with the current version of the MMS.
+- : Contains a string with the message identification of the MMS as defined in [ETSI TS 123 140].
+- : Contains a string with the address information of the terminals or the entities sending the MMS, the specific format shall follow the address definition of MMS in [ETSI TS 123 140].
+- : Contains a string with the address information of the terminals or the entities receiving the MMS, the specific format shall follow the address definition of MMS in [ETSI TS 123 140].
+- : Contains a string with the class of the MMS, e.g., personal, advertisement, informational or auto as defined in [ETSI TS 123 140].
+- : Contains a string with the date and time as the MMS is handled.
+- : Contains a string with the priority of the MMS when handled, which might be "low", "normal" or "high".
+- : Contains a string with the subject of the MMS.
+- : Contains a string with the current status of the MMS, which might be "Draft", "Sent", "New", "Retrieved", "Forwarded" as defined in [ETSI TS 123 140].
+- : Contains a string with any extra descriptive information of the MMS if supported by the terminals or the entities.
+
+## 10.5 Other
+
+XML syntax for additional user data is for further study.
+
+
+
+# SERIES OF ITU-T RECOMMENDATIONS
+
+| | |
+|-----------------|---------------------------------------------------------------------------------------------|
+| Series A | Organization of the work of ITU-T |
+| Series D | General tariff principles |
+| Series E | Overall network operation, telephone service, service operation and human factors |
+| Series F | Non-telephone telecommunication services |
+| Series G | Transmission systems and media, digital systems and networks |
+| Series H | Audiovisual and multimedia systems |
+| Series I | Integrated services digital network |
+| Series J | Cable networks and transmission of television, sound programme and other multimedia signals |
+| Series K | Protection against interference |
+| Series L | Construction, installation and protection of cables and other elements of outside plant |
+| Series M | Telecommunication management, including TMN and network maintenance |
+| Series N | Maintenance: international sound programme and television transmission circuits |
+| Series O | Specifications of measuring equipment |
+| Series P | Terminals and subjective and objective assessment methods |
+| Series Q | Switching and signalling |
+| Series R | Telegraph transmission |
+| Series S | Telegraph services terminal equipment |
+| Series T | Terminals for telematic services |
+| Series U | Telegraph switching |
+| Series V | Data communication over the telephone network |
+| Series X | Data networks, open system communications and security |
+| Series Y | Global information infrastructure, Internet protocol aspects and next-generation networks |
+| Series Z | Languages and general software aspects for telecommunication systems |
\ No newline at end of file
diff --git a/marked/F/T-REC-F.746.20-202512-I_PDF-E/raw.md b/marked/F/T-REC-F.746.20-202512-I_PDF-E/raw.md
new file mode 100644
index 0000000000000000000000000000000000000000..1cb0ef235ea61e896f50002e19b5c1ba0adf9889
--- /dev/null
+++ b/marked/F/T-REC-F.746.20-202512-I_PDF-E/raw.md
@@ -0,0 +1,466 @@
+
+
+# Recommendation **ITU-T F.746.20 (12/2025)**
+
+SERIES F: Non-telephone telecommunication services
+
+Multimedia services
+
+## --- **Framework for interactive virtual performing arts services**
+
+
+
+The logo of the International Telecommunication Union (ITU) is located in the bottom right corner. It features a blue circular emblem with a stylized globe and the letters 'ITU' in white.
+
+ITU logo
+
+## ITU-T F-SERIES RECOMMENDATIONS **Non-telephone telecommunication services**
+
+| | |
+|-----------------------------------------------------------------|--------------------|
+| TELEGRAPH SERVICE | F.1-F.109 |
+| Operating methods for the international public telegram service | F.1-F.19 |
+| The gentex network | F.20-F.29 |
+| Message switching | F.30-F.39 |
+| The international telemessage service | F.40-F.58 |
+| The international telex service | F.59-F.89 |
+| Statistics and publications on international telegraph services | F.90-F.99 |
+| Scheduled and leased communication services | F.100-F.104 |
+| Phototelegraph service | F.105-F.109 |
+| MOBILE SERVICE | F.110-F.159 |
+| Mobile services and multdestination satellite services | F.110-F.159 |
+| TELEMATIC SERVICES | F.160-F.399 |
+| Public facsimile service | F.160-F.199 |
+| Teletex service | F.200-F.299 |
+| Videotex service | F.300-F.349 |
+| General provisions for telematic services | F.350-F.399 |
+| MESSAGE HANDLING SERVICES | F.400-F.499 |
+| DIRECTORY SERVICES | F.500-F.549 |
+| DOCUMENT COMMUNICATION | F.550-F.599 |
+| Document communication | F.550-F.579 |
+| Programming communication interfaces | F.580-F.599 |
+| DATA TRANSMISSION SERVICES | F.600-F.699 |
+| MULTIMEDIA SERVICES | F.700-F.799 |
+| ISDN SERVICES | F.800-F.849 |
+| UNIVERSAL PERSONAL TELECOMMUNICATION | F.850-F.899 |
+| ACCESSIBILITY AND HUMAN FACTORS | F.900-F.999 |
+
+*For further details, please refer to the list of ITU-T Recommendations.*
+
+# Recommendation ITU-T F.746.20
+
+# Framework for interactive virtual performing arts services
+
+## Summary
+
+Performing arts is a generic term for artistic acts presented in real time on stage for an audience. These performances are rapidly shifting from offline to online virtual environments due to the spread of non-face-to-face culture, influenced by external factors such as the COVID-19 pandemic and the development of digital technologies.
+
+The interactive virtual performing arts services framework is an ICT-based framework that enables stage performances in a virtual environment, allowing performers and audiences to interact through their avatars.
+
+Recommendation ITU-T F.746.20 specifies a framework for interactive virtual performing arts services. The framework establishes common requirements for avatar-based representation, real-time interaction, and coordinated management of the stage, auditorium, assets, and audiences, supported by seamless connectivity and stakeholders. It defines components, data and control architecture, core functional components and an operation model to enable interoperability and comparability of interactive virtual performing arts services across different platforms and providers.
+
+## History\*
+
+| Edition | Recommendation | Approval | Study Group | Unique ID |
+|---------|----------------|------------|-------------|--------------------|
+| 1.0 | ITU-T F.746.20 | 2025-12-14 | 21 | 11.1002/1000/16580 |
+
+## Keywords
+
+ICT-based avatar interaction, virtual performing arts.
+
+---
+
+\* To access the Recommendation, type the URL in the address field of your web browser, followed by the Recommendation's unique ID.
+
+## FOREWORD
+
+The International Telecommunication Union (ITU) is the United Nations specialized agency in the field of telecommunications, and information and communication technologies (ICTs). The ITU Telecommunication Standardization Sector (ITU-T) is a permanent organ of ITU. ITU-T is responsible for studying technical, operating and tariff questions and issuing Recommendations on them with a view to standardizing telecommunications on a worldwide basis.
+
+The World Telecommunication Standardization Assembly (WTSA), which meets every four years, establishes the topics for study by the ITU-T study groups which, in turn, produce Recommendations on these topics.
+
+The approval of ITU-T Recommendations is covered by the procedure laid down in WTSA Resolution 1.
+
+In some areas of information technology which fall within ITU-T's purview, the necessary standards are prepared on a collaborative basis with ISO and IEC.
+
+## NOTE
+
+In this Recommendation, the expression "Administration" is used for conciseness to indicate both a telecommunication administration and a recognized operating agency.
+
+Compliance with this Recommendation is voluntary. However, the Recommendation may contain certain mandatory provisions (to ensure, e.g., interoperability or applicability) and compliance with the Recommendation is achieved when all of these mandatory provisions are met. The words "shall" or some other obligatory language such as "must" and the negative equivalents are used to express requirements. The use of such words does not suggest that compliance with the Recommendation is required of any party.
+
+## INTELLECTUAL PROPERTY RIGHTS
+
+ITU draws attention to the possibility that the practice or implementation of this Recommendation may involve the use of a claimed Intellectual Property Right. ITU takes no position concerning the evidence, validity or applicability of claimed Intellectual Property Rights, whether asserted by ITU members or others outside of the Recommendation development process.
+
+As of the date of approval of this Recommendation, ITU had not received notice of intellectual property, protected by patents/software copyrights, which may be required to implement this Recommendation. However, implementers are cautioned that this may not represent the latest information and are therefore strongly urged to consult the appropriate ITU-T databases available via the ITU-T website at .
+
+© ITU 2026
+
+All rights reserved. No part of this publication may be reproduced, by any means whatsoever, without the prior written permission of ITU.
+
+## Table of Contents
+
+| | Page |
+|---------------------------------------------------------------------------------------------|------|
+| 1 Scope..... | 1 |
+| 2 References..... | 1 |
+| 3 Definitions ..... | 1 |
+| 3.1 Terms defined elsewhere ..... | 1 |
+| 3.2 Terms defined in this Recommendation..... | 2 |
+| 4 Abbreviations and acronyms ..... | 2 |
+| 5 Conventions ..... | 2 |
+| 6 Background..... | 2 |
+| 7 Interactive virtual performing arts services framework..... | 2 |
+| 7.1 System requirements ..... | 3 |
+| 7.2 Stakeholders ..... | 3 |
+| 7.3 Components and roles of the interactive virtual performing arts services framework..... | 5 |
+| 7.4 Data and control architecture..... | 6 |
+| 7.5 Operational model ..... | 9 |
+| Bibliography..... | 12 |
+
+
+
+# Recommendation ITU-T F.746.20
+
+## Framework for interactive virtual performing arts services
+
+## 1 Scope
+
+This Recommendation establishes requirements to enable interoperability and comparability of interactive virtual performing arts systems across different platforms and providers.
+
+This Recommendation specifies the interactive virtual performing arts services framework, including requirements, stakeholders, components, data and control architecture, and operational models.
+
+The scope of this Recommendation includes:
+
+- Requirements for ICT-based interactive virtual performing arts services framework.
+- Definition of stakeholders and framework components.
+- Specification of the control architecture and the operational models for interoperability and consistent interaction.
+
+# 2 References
+
+The following ITU-T Recommendations and other references contain provisions which, through reference in this text, constitute provisions of this Recommendation. At the time of publication, the editions indicated were valid. All Recommendations and other references are subject to revision; users of this Recommendation are therefore encouraged to investigate the possibility of applying the most recent edition of the Recommendations and other references listed below. A list of the currently valid ITU-T Recommendations is regularly published. The reference to a document within this Recommendation does not give it, as a stand-alone document, the status of a Recommendation.
+
+[[ITU-T H.430.1](#)] Recommendation ITU-T H.430.1 (2018), *Requirements for immersive live experience (ILE) services*.
+
+[[ITU-T H.430.2](#)] Recommendation ITU-T H.430.2 (2018), *Architectural framework for immersive live experience (ILE) services*.
+
+[[ITU-T H.430.3](#)] Recommendation ITU-T H.430.3 (V2) (2023), *Service scenario for immersive live experience (ILE)*.
+
+[[ITU-T H.430.4](#)] Recommendation ITU-T H.430.4 (2019), *Service configuration, media transport protocols, signalling information of MPEG media transport for immersive live experience (ILE) systems*.
+
+# 3 Definitions
+
+## 3.1 Terms defined elsewhere
+
+This Recommendation uses the following terms defined elsewhere:
+
+**3.1.1 metaverse** [b-FGMV-20] and [b-ITU FGMV-33]: A converged networked environment integrating digital and physical realities with persistent, shared, and interoperable experiences.
+
+**3.1.2 avatar** [b-FGMV-20] and [b-ITU FGMV-33]: A user's digital representation in a metaverse environment, facilitating interaction and expression.
+
+**3.1.3 service** [b-ITU-T Y.2091]: A set of functions and facilities offered to a user by a provider.
+
+## 3.2 Terms defined in this Recommendation
+
+This Recommendation defines the following terms:
+
+**3.2.1 virtual stage:** A virtual environment that provides a space for presenting performances.
+
+NOTE – The performances of a virtual stage include avatars of performers and stage effects.
+
+**3.2.2 virtual auditorium:** A virtual environment that provides a space for audiences to experience performances through their avatars and interactions.
+
+## 4 Abbreviations and acronyms
+
+This Recommendation uses the following abbreviation and acronym:
+
+ICT Information and Communication Technology
+
+UI User Interface
+
+## 5 Conventions
+
+In this Recommendation:
+
+- The keywords "**is required to**" indicate a requirement which must be strictly followed and from which no deviation is permitted if conformance to this document is to be claimed.
+
+# 6 Background
+
+The performing arts traditionally refer to artistic acts presented in real time on a stage for an audience. With the spread of non-face-to-face culture, driven by external factors such as the COVID-19 pandemic and the development of digital technologies, these performances have increasingly shifted from physical venues to virtual environments.
+
+To reproduce the sense of presence and immersion that is experienced in physical performances, virtual performing arts services require realistic stage composition and interactive accessibility. This includes configuring virtual stages and auditoriums analogous to physical venues, and enabling real-time interaction between performers and audiences through avatars connected over communication networks.
+
+This Recommendation specifies a standardized framework that, with respect to human factors such as avatar-based representation, real-time interaction, and user experience, defines functional components and procedures for interactive virtual performing arts services, including virtual stage composition, stage operation, virtual auditorium composition, auditorium operation, asset management, and audience management.
+
+The metaverse concept addresses broader converged environments integrating digital and physical realities. In contrast, this Recommendation specifies a dedicated framework for interactive virtual performing arts services enabling artistic direction and stage control interfaces, real-time broadcast streaming of the virtual stage, massive audience interaction and virtual audience management. It establishes normative requirements and framework components to support interoperable deployment.
+
+## 7 Interactive virtual performing arts services framework
+
+The framework is an information and communication technology (ICT)-based system that supports stage performances in a virtual environment, allowing performers and audiences to interact through avatars. By defining common requirements and components, this Recommendation establishes a harmonized basis for interoperability, comparability of results, and consistency in the delivery of interactive virtual performing arts services.
+
+This clause specifies system requirements, stakeholders, overall components, the data and control architecture, and the operation model of the interactive virtual performing arts services framework, which enables interoperability and comparability across different platforms and service providers.
+
+## 7.1 System requirements
+
+This clause specifies the system requirements that the interactive virtual performing arts services framework is required to fulfil in order to support an interface that enables an artistic direction and stage control, real-time broadcast streaming of the virtual stage, large-scale audience interaction and virtual audience management. It also specifies requirements for synchronized media exchange using the ITU-T H.430 series Recommendations ([ITU-T H.430.1] [ITU-T H.430.2] [ITU-T H.430.3] [ITU-T H.430.4]), and avatar representation compatibility using the ITU-T FG-MV deliverables:
+
+- The system is required to ensure interoperability and consistent real-time exchange of audio, video, and motion data among performer and audience environments, utilizing immersive media transport and synchronization mechanisms ([ITU-T H.430.1] [ITU-T H.430.2] [ITU-T H.430.3] [ITU-T H.430.4]).
+
+NOTE 1 – This requirement refers to clause 6 in [ITU-T H.430.4] for synchronization. Additional mechanisms supporting immersive media transport and overall architecture refers to the ITU-T H.430 series Recommendations ([ITU-T H.430.1] [ITU-T H.430.2] [ITU-T H.430.3] [ITU-T H.430.4]).
+
+- The system is required to ensure compatibility with avatar representation frameworks in order to enable integration and consistent behaviour of performer and audience avatars within the virtual performance environment.
+
+NOTE 2 – This requirement is related to the specification of metaverse interoperability [b-FGMV-19] [b-FGMV-42] [b-FGMV-43].
+
+- The system is required to support an interface that enables an artistic director to manage and control performance flow, stage effects, and synchronization among performers, audiences, and digital assets in real time.
+- The system is required to support stage management interface for real-time broadcast streaming of the virtual stage for synchronized delivery of performance scenes to multiple audiences.
+- The system is required to support virtual audience management interface, including registration, authentication, admission control, and participation data management.
+
+While building upon existing immersive media transport and avatar representation frameworks, this Recommendation defines additional requirements for an interface that enables an artistic direction and stage control, real-time broadcast streaming of the virtual stage, large-scale audience interaction, and virtual audience management, which are not specified in [ITU-T H.430.1] [ITU-T H.430.2] [ITU-T H.430.3] [ITU-T H.430.4].
+
+## 7.2 Stakeholders
+
+This clause identifies stakeholders and summarizes their functions. Table 1 provides role-level descriptions:
+
+- Performer: generates artistic content represented as avatars on the virtual stage.
+- Audience: consumes and interacts with performance content (passive or interactive) and may broadcast the performance.
+- Designer/maker: provides creative assets (stage design, props, avatar models, lighting, sound, special effects).
+- Director/manager: coordinates artistic and technical processes (direction, stage management, performance direction, lighting/sound operation).
+
+- ICT-based service provider: operates the platform and multimedia communication (e.g., platform operator, streaming operator, platform administrator, platform maintenance provider).
+
+**Table 1 – Stakeholders in interactive virtual performing arts services framework**
+
+| Stakeholders | Subclass | Description |
+|----------------------------------|-------------------------------|-------------------------------------------------------------------------------------------------------------------|
+| Performer | Actor/actress | Person who plays roles for virtual performing arts |
+| | Dancer | Person who expresses body movements in virtual performing arts |
+| | Musician | Person who plays music in virtual performing arts |
+| | Singer | Person who sings in virtual performing arts |
+| Audience | One-way audience | Audience who participates in a one-way manner (no real-time interaction) |
+| | Interactive audience | Audience who interactively communicates |
+| | Streamer | Audience who broadcasts virtual performing arts |
+| Designer/
maker | Set designer | Person who designs equipment for virtual performance stages |
+| | Property maker | Person who makes props for virtual performance stages |
+| | Avatar designer | Person who designs and creates avatars for virtual performance stages |
+| | Special effects designer | Person who creates special effects for virtual performance stages |
+| | Lighting designer | Person who designs concept of light and creates an action plan in the production of performance |
+| | Sound designer | Person who designs concept of sound and creates an action plan in the production of performance |
+| Director/
manager | Main director | Person responsible for integrating and coordinating the entire artistic field of performance production |
+| | Assistant director | Person who assists in artistic process of directing |
+| | Stage manager | Person responsible for coordinating lighting, sound, stage equipment, stage transitions, and performance progress |
+| | Performance director | Person who directs live actors for motion capture and manages avatar movements |
+| | Special effects operator | Person who operates special effects equipment for virtual performing arts |
+| | Lighting director | Person who designs the lighting concept and creates an action plan for the performance production |
+| | Sound director | Person who designs concept of sound and creates an action plan for the performance production |
+| ICT-based
service
provider | Platform operator | Person who operates platform and multimedia communication |
+| | Streaming operator | Person who runs streaming and ensures synchronization |
+| | Platform administrator | Person who manages authorization and administration |
+| | Platform maintenance provider | Person who provides maintenance for the platform and the multimedia communication |
+
+## 7.3 Components and roles of the interactive virtual performing arts services framework
+
+Components and roles of the framework are provided in Figure 1. Clauses 7.4 and 7.5 specify the supporting architecture and procedures. For the purpose of description, these eight components, namely direction orchestration, virtual stage composition, stage operation, virtual auditorium, auditorium operation, audience management, asset management and multimedia communication, are grouped into an application subsystem and a communication subsystem as shown in Figure 1, which correspond to the operational entities specified in clause 7.5. In Figure 1, solid rectangles represent components, while dashed rectangles represent roles within each component.
+
+
+
+Figure 1: Components and roles of interactive virtual performing arts services framework. The diagram shows a hierarchical structure of components and roles. At the top is 'UI direction orchestration' (solid rectangle) containing 'Stage direction', 'Scene synchronization', and 'Audience coordination' (dashed rectangles). Below this are four main components: 'Asset management' (solid), 'UI stage operation' (solid), 'UI auditorium operation' (solid), and 'Audience management' (solid). 'Asset management' contains 'Avatar asset', 'Stage asset', 'Effects asset', and 'Interaction asset' (dashed). 'UI stage operation' contains 'Virtual stage composition' (solid), which includes 'Stage effects' (solid) with 'Lighting effects', 'Sound effects', 'Special effects', and 'Video walls' (dashed), and 'Performer avatars' (solid) with 'Motion', 'Voice', 'Appearance', and 'Facial expression' (dashed). 'UI auditorium operation' contains 'Virtual auditorium composition' (solid), which includes 'Auditorium interface' (solid) with 'Props interaction', 'Viewpoint switch', 'Billboard interaction', and 'Spatial movement' (dashed), and 'Audience avatars' (solid) with 'Motion', 'Voice', 'Appearance', and 'Facial expression' (dashed). 'Audience management' contains 'User management', 'Payment management', and 'Admission management' (dashed). At the bottom is 'Multimedia communication' (solid) containing 'Interactive streaming' and 'One-way streaming' (dashed). The top section is labeled 'Application subsystem' and the bottom 'Communication subsystem'. Arrows indicate flow from top to middle and bidirectional flow between middle and bottom. A small code 'F.746.20(25)' is in the bottom right corner of the diagram area.
+
+Figure 1 – Components and roles of interactive virtual performing arts services framework
+
+### 7.3.1 Virtual stage composition and UI stage operation
+
+The virtual stage composition and user interface (UI) stage operation process performers' motion and audio data and applies them to avatar models. They synthesize and render stage scenes with avatar motion, voice, appearance, and facial expressions, and support stage effects including lighting, sound, special effects, and video walls.
+
+### 7.3.2 Virtual auditorium composition and UI auditorium operation
+
+The virtual auditorium composition and UI auditorium operation process audience motion, voice, appearance, and facial expressions, apply them to audience avatars, and render the auditorium scene by combining these data with environmental and interaction elements. They support interaction functions such as props interaction, viewpoint switching, billboard interaction, and spatial movement.
+
+#### 7.3.3 Audience management
+
+The audience management component performs audience-related administrative functions. It provides user registration, authentication, and admission control, and processes payment and profile
+
+data. This information is provided to the virtual auditorium composition via the auditorium operation to ensure consistent audience representation and interaction.
+
+#### **7.3.4 Asset management**
+
+The asset management also supplies the required assets to other components in a synchronized manner. asset management manages digital assets used in the virtual stage composition and virtual auditorium composition. It stores and updates stage, prop, and avatar models, and controls lighting, sound, special effects, and video walls. It also supplies assets to other components in a synchronized manner.
+
+#### **7.3.5 UI direction orchestration**
+
+The direction orchestration coordinates the overall operation of the framework. It manages stage direction, performance flow, effect triggering, and synchronization between the virtual stage composition and virtual auditorium composition. It also coordinates audience interaction to align responses with stage events and ensures coherent operation across all components, including multimedia communication and management functions.
+
+#### **7.3.6 Multimedia communication**
+
+The multimedia communication integrates and delivers data streams among components. It supports interactive communication and one-way delivery and provides data mixing and visualization to ensure consistent representation across the virtual stage composition and the virtual auditorium composition.
+
+## **7.4 Data and control architecture**
+
+This clause specifies the data and control architecture of the interactive virtual performing arts services framework. Figures 2 and 3 illustrate the architecture from two complementary perspectives. Figure 2 shows the application subsystem flows among functional entities such as virtual stage composition, stage operation, virtual auditorium composition, auditorium operation, audience management, asset management, and direction orchestration. Figure 3 shows the communication subsystem flows, which are provided by multimedia communication through storage, service, and session functions that enable the transfer and synchronization of data used by the application subsystem entities. Together, Figures 2 and 3 specify the overall data and control architecture of the framework, in which the communication subsystem provides storage, session and delivery functions that transport, synchronize and manage data and control flows between application subsystem entities, enabling consistent and reliable operation. In these figures, solid arrows denote control flows, dashed arrows denote data flows, rectangles denote data entities, rounded rectangles denote functional entities, and human figures denote actors representing sources or recipients of data and control flows.
+
+#### **7.4.1 Application subsystem flows**
+
+This clause specifies the data and control flows among functional entities of the interactive virtual performing arts services framework. These flows enable consistent representation and synchronized interaction between virtual stage composition, UI stage operation, virtual auditorium composition, UI auditorium operation, audience management, asset management, and UI direction orchestration.
+
+
+
+Figure 2 – Data and control architecture of application subsystem. This block diagram illustrates the flow of data and control signals between various components. On the left, a 'Performer' provides 'Performer motion data' and 'Performer audio data' to the 'UI Stage Operation'. A 'Designer/ Maker' provides 'Stage/ Effects asset data', 'Avatar asset data', and 'Interaction asset data' to 'Asset Management'. On the right, an 'Audience' provides 'Audience motion data', 'Audience message data', 'Audience position data', and 'User payment/ Admission data' to 'UI Auditorium Operation'. The central 'UI Direction Orchestration' (containing a 'Director/ Manager' icon) receives data from all four operations: 'UI Stage Operation', 'Virtual Stage Composition', 'Virtual Auditorium Composition', and 'UI Auditorium Operation'. It also receives data from 'Asset Management' and 'Audience Management'. The 'UI Stage Operation' and 'UI Auditorium Operation' both have bidirectional connections to the 'Virtual Stage Composition' and 'Virtual Auditorium Composition'. The 'UI Auditorium Operation' also has a bidirectional connection to 'Audience Management'. The 'UI Direction Orchestration' has bidirectional connections to the 'UI Stage Operation', 'Virtual Stage Composition', 'Virtual Auditorium Composition', and 'UI Auditorium Operation'. The 'UI Direction Orchestration' also has bidirectional connections to 'Asset Management' and 'Audience Management'. The 'UI Direction Orchestration' is connected to the 'Director/ Manager' icon. The 'UI Direction Orchestration' is connected to the 'Director/ Manager' icon. The 'UI Direction Orchestration' is connected to the 'Director/ Manager' icon.
+
+**Figure 2 – Data and control architecture of application subsystem**
+
+##### 7.4.1.1 Data transmission procedure
+
+The data transmission procedure specifies how data are transferred among functional entities:
+
+- Motion-capture and audio data generated by the performer are transferred to the Virtual stage composition via the UI stage operation.
+- Stage, props and avatar model data generated by designers and makers are managed by Asset Management and are delivered to the virtual stage composition and the virtual auditorium composition via the UI stage operation as required.
+- Audience-reaction data, including gesture, message and position are transferred to the virtual auditorium composition via the UI auditorium operation for representation and interaction control.
+- Admission, payment and profile data are processed by audience management and are provided to the virtual auditorium composition via the UI auditorium operation when necessary.
+- Streaming data generated by the virtual stage composition and the virtual auditorium composition are delivered to performers and audiences.
+- Control-related data associated with each operation of the UI direction orchestration are received from relevant functional entities to maintain synchronized coordination and system feedback.
+
+##### 7.4.1.2 Control procedure
+
+The control procedure specifies how control functions are coordinated among functional entities:
+
+- Virtual stage composition applies performer data to avatars for reproduction.
+- Asset management provides stage, props and avatar models to the virtual stage composition and the virtual auditorium composition via the stage Operation.
+- Virtual auditorium composition processes audience data and manages the auditorium state.
+- Synchronization, scene control and effect triggering is exchanged among the virtual stage composition, the virtual auditorium composition and the asset management.
+- The Direction Orchestration coordinates these control flows by providing stage direction operation, scene synchronization and audience interaction coordination.
+
+##### 7.4.1.3 Functional entities
+
+The functional entities perform the following tasks in supporting subsystem operation:
+
+- Virtual stage composition and stage operation process performer motion and audio data, applies them to avatar models and render stage scenes with stage effects.
+- Virtual auditorium composition and auditorium operation represent audience avatars and supports props interaction, viewpoint switching, billboard interaction and spatial movement.
+- Audience management handles user registration, authentication, admission and payment, and provides user data to the virtual auditorium composition.
+- Asset management maintains digital assets such as stage, props and avatar models and controls lighting, sound, special effects and video walls.
+- Direction orchestration coordinates the overall framework by managing stage direction, synchronizing scenes between stage and auditorium, and aligning audience interaction with stage events.
+
+#### 7.4.2 Communication subsystem flows
+
+This clause specifies the communication subsystem data and control flows that support the functional entities of the interactive virtual performing arts services framework. These flows are provided by the multimedia communication, which consists of storage repository, service delivery and session coordination, supporting virtual stage delivery, interactive communication and virtual auditorium delivery. The communication subsystem flows enable motion, audio, asset and interaction data to be consistently stored, processed and delivered, and channels to be established and maintained for synchronized operation across virtual stage composition, virtual auditorium composition, audience management, asset management and direction orchestration.
+
+
+
+The diagram illustrates the data and control architecture of the communication subsystem. It is organized into three main vertical columns:
+
+
+- Storage repository:** Contains four stacked boxes representing data types: 'User payment/admission data', 'Audience motion/message/position data', 'Performer motion/audio data', and 'Stage/Avatar/Interaction asset data'.
+- Service delivery:** Contains three stacked boxes representing functions: 'Virtual auditorium delivery', 'Interactive communication', and 'Virtual stage delivery'.
+- Session coordination:** Contains four stacked boxes representing channels: 'Audience channel', 'Interaction channel', 'Performer channel', and 'Asset channel'.
+
+ Data flow is indicated by arrows:
+
+
+- Dashed arrows point from each of the four data types in the 'Storage repository' to the 'Virtual auditorium delivery', 'Interactive communication', and 'Virtual stage delivery' functions.
+- Solid arrows point from each of the three 'Service delivery' functions to each of the four 'Session coordination' channels.
+
+ At the bottom left, there is an icon of a person labeled 'ICT-based service provider'. At the bottom right, the text 'F.746.20(25)' is present.
+
+Figure 3: Data and control architecture of communication subsystem. The diagram shows three main components: Storage repository, Service delivery, and Session coordination. The Storage repository contains four data types: User payment/admission data, Audience motion/message/position data, Performer motion/audio data, and Stage/Avatar/Interaction asset data. The Service delivery contains three functions: Virtual auditorium delivery, Interactive communication, and Virtual stage delivery. The Session coordination contains four channels: Audience channel, Interaction channel, Performer channel, and Asset channel. Arrows indicate data flow from the Storage repository to the Service delivery functions and from the Service delivery functions to the Session coordination channels. A legend at the bottom shows an icon for 'ICT-based service provider' and the code 'F.746.20(25)'.
+
+**Figure 3 – Data and control architecture of communication subsystem**
+
+##### 7.4.2.1 Data transmission procedure
+
+The data transmission procedure specifies how data types are transmitted within the multimedia communication:
+
+- Performer motion and audio data are transmitted to service delivery hosting the virtual stage delivery function, where they are combined with stage effects.
+- Audience-reaction data, including gestures, messages and positions, are transmitted to service delivery hosting the interactive communication function, where they are mixed with performer data.
+
+- User payment and admission data, as provided by audience management, are transported via the multimedia communication to service delivery hosting the virtual auditorium delivery function.
+- Asset data, including stage, effects, avatars and interaction assets, are transmitted to the storage repository of the multimedia communication and are delivered to service delivery as required.
+- Control-related data exchanged between service delivery functions and session coordination functions, as well as storage repository data, are subsequently delivered to the session coordination functions through the service delivery functions.
+
+##### 7.4.2.2 Control procedure
+
+The control procedure specifies how session coordination establishes and manages channels in coordination with service delivery within the multimedia communication, as shown in Figure 3:
+
+- Session coordination establishes and maintains the channels supporting the three service delivery functions: virtual stage delivery, interactive communication, and virtual auditorium delivery.
+- Coordination actions include channel establishment, synchronization of data streams and effect triggering to ensure consistent rendering of stage and auditorium environments.
+- Each service delivery function operates its associated channel through session coordination: virtual stage delivery for the performer channel, interactive communication for the interaction channel, and virtual auditorium delivery for the audience channel.
+
+##### 7.4.2.3 Functional entities
+
+The functional entities specify the tasks that are performed within the multimedia communication:
+
+- Storage repository provides repositories for performer motion and audio data, audience-reaction data, user admission data and performance asset data.
+- Service delivery supports virtual stage delivery, interactive communication and virtual auditorium delivery, and processes and forwards the corresponding data streams.
+- Session coordination establishes and maintains the required channels for these services and ensures that data and control flows are delivered reliably and in synchronization across the framework.
+
+## 7.5 Operational model
+
+This clause specifies the operational model of the interactive virtual performing arts services framework. Figure 4 illustrates the operational interactions among the functional entities, which are stage operation, direction orchestration, virtual stage and virtual auditorium composition, and auditorium operation. The operational model specifies how performance data, model data, stage scenes and audience reaction data are exchanged among these entities, and how coordination is achieved through functions such as system start-up and control, stage mixing, auditorium mixing, visualization of stage scenes and visualization of updated auditorium scenes. In Figure 4, solid arrows denote control flows and dashed arrows denote data flows, while rectangles denote functional entities and data labels identify the information exchanged between entities.
+
+
+
+Sequence diagram illustrating the operational model of interactive virtual performing arts services framework. The diagram shows four lifelines: UI Stage Operation, UI Direction Orchestration, Virtual Stage and Virtual Auditorium Compositions, and UI Auditorium Operation. The sequence of interactions is as follows: 1. UI Direction Orchestration sends 'Request initiation' to Virtual Stage and Virtual Auditorium Compositions. 2. Virtual Stage and Virtual Auditorium Compositions performs 'Configure asset' and 'Initiate connection'. 3. Virtual Stage and Virtual Auditorium Compositions sends 'Confirm completion' to UI Direction Orchestration. 4. UI Direction Orchestration sends 'Request performance' to UI Stage Operation. 5. UI Stage Operation sends 'Send performance data' to Virtual Stage and Virtual Auditorium Compositions. 6. Virtual Stage and Virtual Auditorium Compositions performs 'Mix stage'. 7. Virtual Stage and Virtual Auditorium Compositions sends 'Send stage data' to UI Auditorium Operation. 8. UI Auditorium Operation performs 'Visualize stage'. 9. UI Auditorium Operation sends 'Send reaction data' to Virtual Stage and Virtual Auditorium Compositions. 10. Virtual Stage and Virtual Auditorium Compositions performs 'Mix auditorium'. 11. Virtual Stage and Virtual Auditorium Compositions sends 'Send auditorium data' to UI Auditorium Operation. 12. UI Auditorium Operation performs 'Visualize auditorium'. 13. Virtual Stage and Virtual Auditorium Compositions sends 'Send auditorium data' to UI Stage Operation. 14. UI Stage Operation performs 'Visualize auditorium'. A label F.746.20(25) is present at the bottom right.
+
+**Figure 4 – Operational model of interactive virtual performing arts services framework**
+
+#### 7.5.1 Functional entities
+
+The functional entities shown in Figure 4 exchange data and control flows to realize the operational model of the framework:
+
+- UI stage operation processes performance data and applies it to avatar models and stage effects for scene generation.
+- UI direction orchestration requests the initiation of asset and connection as pre-operational steps, and issues stage control, manages synchronization of data and scenes, and coordinate stage and auditorium mixing.
+- Virtual stage and virtual auditorium compositions perform asset configuration and connection initiation upon request, and synthesize and update scenes by combining processed performance data, model data and audience reaction data through stage and auditorium mixing.
+- UI auditorium operation renders stage and auditorium scenes and collects audience reaction data for feedback.
+
+#### 7.5.2 Behaviour
+
+The behaviour defines the sequence of actions performed by the functional entities in exchanging data and control flows:
+
+- UI direction orchestration requests the initiation of asset and connection as pre-operational steps.
+- Virtual stage and virtual auditorium compositions perform asset and connection initiation upon request and confirm completion to UI direction orchestration.
+- After confirmation, UI direction orchestration sends control to UI stage operation.
+
+- UI stage operation processes performance and model data and delivers the processed data to virtual stage and virtual auditorium compositions.
+- Virtual stage and virtual auditorium compositions perform stage mixing to generate a stage scene.
+- The generated stage scene is delivered to UI auditorium operation, which renders the stage scene to the audience.
+- UI auditorium operation collects audience reaction data and provides it to virtual stage and virtual auditorium compositions.
+- Virtual stage and virtual auditorium compositions perform auditorium mixing by combining the stage scene with audience reaction data to generate an updated auditorium scene.
+- UI auditorium operation renders the updated auditorium scene to the audience.
+
+## Bibliography
+
+- [b-ITU-T Y.2091] Recommendation ITU-T Y.2091 (2011), *Terms and definitions for next generation networks*.
+- [b-FGMV-19] ITU-T Focus Group on metaverse deliverable number 19 (Technical Specification) (2023), *Service scenarios and high-level requirements for metaverse cross-platform interoperability*.
+- [b-FGMV-20] ITU-T Focus Group on Metaverse deliverable number 20 (Technical Specification) (2023), *Definition of metaverse*.
+- [b-FGMV-33] ITU-T Focus Group on Metaverse deliverable number 33 (Technical Specification) (2024), *Glossary for metaverse*.
+- [b-FGMV-42] ITU-T Focus Group on metaverse deliverable number 42 (Technical Report) (2024), *Interoperability of identity of things across metaverse platforms*.
+- [b-FGMV-43] ITU-T Focus Group on metaverse deliverable number 43 (Technical Specification) (2024), *High-level interoperability architecture for cross-platform metaverse*.
+
+
+
+## SERIES OF ITU-T RECOMMENDATIONS
+
+| | |
+|-----------------|-----------------------------------------------------------------------------------------------------------------------------------------------------------|
+| Series A | Organization of the work of ITU-T |
+| Series D | Tariff and accounting principles and international telecommunication/ICT economic and policy issues |
+| Series E | Overall network operation, telephone service, service operation and human factors |
+| Series F | Non-telephone telecommunication services |
+| Series G | Transmission systems and media, digital systems and networks |
+| Series H | Audiovisual and multimedia systems |
+| Series I | Integrated services digital network |
+| Series J | Cable networks and transmission of television, sound programme and other multimedia signals |
+| Series K | Protection against interference |
+| Series L | Environment and ICTs, climate change, e-waste, energy efficiency; construction, installation and protection of cables and other elements of outside plant |
+| Series M | Telecommunication management, including TMN and network maintenance |
+| Series N | Maintenance: international sound programme and television transmission circuits |
+| Series O | Specifications of measuring equipment |
+| Series P | Telephone transmission quality, telephone installations, local line networks |
+| Series Q | Switching and signalling, and associated measurements and tests |
+| Series R | Telegraph transmission |
+| Series S | Telegraph services terminal equipment |
+| Series T | Terminals for telematic services |
+| Series U | Telegraph switching |
+| Series V | Data communication over the telephone network |
+| Series X | Data networks, open system communications and security |
+| Series Y | Global information infrastructure, Internet protocol aspects, next-generation networks, Internet of Things and smart cities |
+| Series Z | Languages and general software aspects for telecommunication systems |
\ No newline at end of file
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+
+
+# Recommendation **ITU-T F.746.21 (12/2025)**
+
+SERIES F: Non-telephone telecommunication services
+
+Multimedia services
+
+---
+
+## **Requirements for intelligent user interface services for persons with age-related disabilities**
+
+
+
+The logo of the International Telecommunication Union (ITU) is located in the bottom right corner. It features a blue circular emblem with a stylized globe and the letters 'ITU' in white.
+
+ITU logo
+
+## ITU-T F-SERIES RECOMMENDATIONS **Non-telephone telecommunication services**
+
+| | |
+|-----------------------------------------------------------------|--------------------|
+| TELEGRAPH SERVICE | F.1-F.109 |
+| Operating methods for the international public telegram service | F.1-F.19 |
+| The gentex network | F.20-F.29 |
+| Message switching | F.30-F.39 |
+| The international telemessage service | F.40-F.58 |
+| The international telex service | F.59-F.89 |
+| Statistics and publications on international telegraph services | F.90-F.99 |
+| Scheduled and leased communication services | F.100-F.104 |
+| Phototelegraph service | F.105-F.109 |
+| MOBILE SERVICE | F.110-F.159 |
+| Mobile services and multdestination satellite services | F.110-F.159 |
+| TELEMATIC SERVICES | F.160-F.399 |
+| Public facsimile service | F.160-F.199 |
+| Teletex service | F.200-F.299 |
+| Videotex service | F.300-F.349 |
+| General provisions for telematic services | F.350-F.399 |
+| MESSAGE HANDLING SERVICES | F.400-F.499 |
+| DIRECTORY SERVICES | F.500-F.549 |
+| DOCUMENT COMMUNICATION | F.550-F.599 |
+| Document communication | F.550-F.579 |
+| Programming communication interfaces | F.580-F.599 |
+| DATA TRANSMISSION SERVICES | F.600-F.699 |
+| MULTIMEDIA SERVICES | F.700-F.799 |
+| ISDN SERVICES | F.800-F.849 |
+| UNIVERSAL PERSONAL TELECOMMUNICATION | F.850-F.899 |
+| ACCESSIBILITY AND HUMAN FACTORS | F.900-F.999 |
+
+*For further details, please refer to the list of ITU-T Recommendations.*
+
+# Recommendation ITU-T F.746.21
+
+# Requirements for intelligent user interface services for persons with age-related disabilities
+
+## Summary
+
+Owing to the recent development of artificial intelligence (AI), especially deep learning technology, multimodal user interfaces (UIs) are increasingly used as intelligent tools for systems requiring improved usability. Human-machine interaction is also critical in the domains of services for persons with age-related disabilities, including various devices. Therefore, UIs should be designed for various users and their tasks, based on the characteristics of users, tasks and devices. The AI technologies will help to devise trustworthy and convenient UIs in the corresponding care services for persons with age-related disabilities.
+
+Recommendation ITU-T F.746.21 introduces intelligent user interface (IUI) services for persons with age-related disabilities. In order to support these various IUI services, it reviews use cases and proposes requirements, and then defines common components and characteristics of IUI services.
+
+## History\*
+
+| Edition | Recommendation | Approval | Study Group | Unique ID |
+|---------|----------------|------------|-------------|--------------------|
+| 1.0 | ITU-T F.746.21 | 2025-12-14 | 21 | 11.1002/1000/16581 |
+
+## Keywords
+
+Accessibility, intelligent user interface (IUI), multimodal interaction, services for persons with age-related disabilities.
+
+---
+
+\* To access the Recommendation, type the URL in the address field of your web browser, followed by the Recommendation's unique ID.
+
+## FOREWORD
+
+The International Telecommunication Union (ITU) is the United Nations specialized agency in the field of telecommunications, and information and communication technologies (ICTs). The ITU Telecommunication Standardization Sector (ITU-T) is a permanent organ of ITU. ITU-T is responsible for studying technical, operating and tariff questions and issuing Recommendations on them with a view to standardizing telecommunications on a worldwide basis.
+
+The World Telecommunication Standardization Assembly (WTSA), which meets every four years, establishes the topics for study by the ITU-T study groups which, in turn, produce Recommendations on these topics.
+
+The approval of ITU-T Recommendations is covered by the procedure laid down in WTSA Resolution 1.
+
+In some areas of information technology which fall within ITU-T's purview, the necessary standards are prepared on a collaborative basis with ISO and IEC.
+
+### NOTE
+
+In this Recommendation, the expression "Administration" is used for conciseness to indicate both a telecommunication administration and a recognized operating agency.
+
+Compliance with this Recommendation is voluntary. However, the Recommendation may contain certain mandatory provisions (to ensure, e.g., interoperability or applicability) and compliance with the Recommendation is achieved when all of these mandatory provisions are met. The words "shall" or some other obligatory language such as "must" and the negative equivalents are used to express requirements. The use of such words does not suggest that compliance with the Recommendation is required of any party.
+
+## INTELLECTUAL PROPERTY RIGHTS
+
+ITU draws attention to the possibility that the practice or implementation of this Recommendation may involve the use of a claimed Intellectual Property Right. ITU takes no position concerning the evidence, validity or applicability of claimed Intellectual Property Rights, whether asserted by ITU members or others outside of the Recommendation development process.
+
+As of the date of approval of this Recommendation, ITU had not received notice of intellectual property, protected by patents/software copyrights, which may be required to implement this Recommendation. However, implementers are cautioned that this may not represent the latest information and are therefore strongly urged to consult the appropriate ITU-T databases available via the ITU-T website at .
+
+© ITU 2026
+
+All rights reserved. No part of this publication may be reproduced, by any means whatsoever, without the prior written permission of ITU.
+
+## Table of Contents
+
+| | Page |
+|----------------------------------------------------------------------------------------------|------|
+| 1 Scope..... | 1 |
+| 2 References..... | 1 |
+| 3 Definitions ..... | 1 |
+| 3.1 Terms defined elsewhere ..... | 1 |
+| 3.2 Terms defined in this Recommendation ..... | 2 |
+| 4 Abbreviations and acronyms ..... | 2 |
+| 5 Conventions ..... | 2 |
+| 6 Background..... | 2 |
+| 7 Characteristics of IUI services for persons with age-related disabilities..... | 3 |
+| 7.1 Consideration of age-related characteristics..... | 3 |
+| 7.2 Intelligent user interface features for persons with age-related disabilities ... | 4 |
+| 7.3 Service models for persons with age-related disabilities ..... | 5 |
+| 8 Conceptual model of IUI for persons with age-related disabilities care systems..... | 9 |
+| 8.1 Components of the conceptual model ..... | 9 |
+| 8.2 Input and output module..... | 10 |
+| 8.3 Data and interaction flow ..... | 11 |
+| 8.4 Conceptual model diagram..... | 11 |
+| 9 Requirements for common components and characteristics of the intelligent UI service ..... | 12 |
+| 9.1 Requirements for common components ..... | 12 |
+| 9.2 Requirements for common characteristics ..... | 13 |
+| 10 Intelligent UI service requirements from a hardware perspective..... | 14 |
+| 11 Intelligent UI service requirements from a software perspective ..... | 14 |
+| Bibliography..... | 16 |
+
+
+
+## Requirements for intelligent user interface services for persons with age-related disabilities
+
+## 1 Scope
+
+This Recommendation specifies intelligent user interface (IUI) services for persons with age-related disabilities, reviews use cases and proposes requirements, and then defines the components and characteristics.
+
+The scope of this Recommendation includes:
+
+- Specification of IUI services for persons with age-related disabilities.
+- Use cases and requirements of IUI services for persons with age-related disabilities.
+- Service components and characteristics of IUI services for persons with age-related disabilities.
+
+## 2 References
+
+The following ITU-T Recommendations and other references contain provisions which, through reference in this text, constitute provisions of this Recommendation. At the time of publication, the editions indicated were valid. All Recommendations and other references are subject to revision; users of this Recommendation are therefore encouraged to investigate the possibility of applying the most recent edition of the Recommendations and other references listed below. A list of the currently valid ITU-T Recommendations is regularly published. The reference to a document within this Recommendation does not give it, as a stand-alone document, the status of a Recommendation.
+
+None.
+
+## 3 Definitions
+
+### 3.1 Terms defined elsewhere
+
+This Recommendation uses the following terms defined elsewhere:
+
+**3.1.1 user interface (UI)** [b-ITU-T F.902]: Software and hardware components through which a user can interact with a system.
+
+**3.1.2 artificial emotional intelligence (AEI)** [b-ITU-T H.862.6]: A multimodal user interface (UI) based on emotion analysis with some properties and illustrations and data.
+
+**3.1.3 machine learning (ML)** [b-ITU-T Y.3172]: Processes that enable computational systems to understand data and gain knowledge from it without necessarily being explicitly programmed.
+
+NOTE 1 – Definition adapted from [b-ETSI GR ENI 004].
+
+NOTE 2 – Supervised machine learning and unsupervised machine learning are two examples of machine learning types.
+
+**3.1.4 person with age-related disabilities** [b-ITU-T F.791]: A person with cognitive or physical disabilities caused by the aging process. Examples are impaired eyesight, deafness in varying degrees, reduced mobility or cognitive abilities.
+
+### 3.2 Terms defined in this Recommendation
+
+This Recommendation defines the following terms:
+
+**3.2.1 intelligence user interface:** A user interface that uses artificial intelligence (AI) to adapt to the user's needs and context.
+
+**3.2.2 multimodal interaction:** An interaction method using more than one input or output mode.
+
+## 4 Abbreviations and acronyms
+
+This Recommendation uses the following abbreviations and acronyms:
+
+AEI Artificial Emotional Intelligence
+
+AI Artificial Intelligence
+
+IUI Intelligent User Interface
+
+ML Machine Learning
+
+UI User Interface
+
+UX User Experience
+
+VUI Voice User Interface
+
+## 5 Conventions
+
+In this Recommendation:
+
+The keywords "**is required to**" indicate a requirement which must be strictly followed and from which no deviation is permitted if conformance to this document is to be claimed.
+
+The keywords "**is recommended**" indicate a requirement which is recommended but which is not absolutely required. Thus, this requirement need not be present to claim conformance.
+
+## 6 Background
+
+User interface (UI) services for persons with age-related disabilities encompass a comprehensive set of functions designed to address their unique needs and challenges. These services leverage AI technologies, particularly deep learning, to provide intuitive, accessible, and user-friendly interfaces that enhance the user experience (UX) and quality of care for persons with age-related disabilities individuals.
+
+Owing to the recent development of AI, especially deep learning technology, multimodal UIs tend to be used as an intelligent tool for different systems that require usability of human factors. Human-machine interaction is also critical in the domains of services for persons with age-related disabilities, including different devices in terms of usability. Therefore, UI should be designed for a wide range of different users and their tasks in the systems based on the characteristics of users, tasks and devices. The IUI should reflect the characteristics of different users and tasks so that the information can be treated and processed appropriately, in a trustworthy manner, and with ease of use in the services for persons with age-related disabilities. AI technology will be of help to devise such convenient and trustworthy UIs in the corresponding elder care systems.
+
+UI services for persons with age-related disabilities are continually evolving, driven by ongoing research and development in AI and human-computer interaction. The focus is on creating interfaces that are adaptive, responsive, adaptable, and empowering, catering to the specific needs and preferences of persons with age-related disabilities. The ultimate goal is to enhance their quality of life, promote independence, and provide comprehensive support for their physical, cognitive, and emotional well-being.
+
+## **7 Characteristics of IUI services for persons with age-related disabilities**
+
+IUI services are recommended to be designed with consideration of the diverse physical, cognitive, sensory, and psychological/emotional characteristics of persons with age-related disabilities. These characteristics significantly affect UX, including accessibility, ease of use, and emotional responsiveness.
+
+Therefore, this clause explains the main considerations and characteristics of IUI services and presents representative service models based on them.
+
+### **7.1 Consideration of age-related characteristics**
+
+It is recommended that the design of UIs for persons with age-related disabilities consider five key characteristics: physical, cognitive, sensory, psychological/emotional, and environmental. Each characteristic reflects different age-related changes and requires tailored design approaches.
+
+#### **1) Physical characteristics**
+
+Physical characteristics include declines in muscular strength, motor skills, reaction speed, and joint flexibility. These changes may cause difficulties in precise manipulation, reduced mobility, and slower responses.
+
+Therefore, it is recommended that interfaces consider the following:
+
+- Use large text and buttons for ease of interaction.
+- Support contactless control methods such as voice and gesture inputs.
+- Minimize requirements for rapid or complex physical actions.
+
+#### **2) Cognitive characteristics**
+
+Cognitive characteristics encompass impairments in memory, attention, decision-making, and information processing speed. Persons with age-related disabilities often face challenges with complex or multi-step procedures.
+
+Therefore, it is recommended that interfaces consider the following:
+
+- Provide step-by-step guidance throughout interactions.
+- Implement predictable and simple menu structures.
+- Use visual emphasis to reinforce learning and reduce cognitive load.
+
+#### **3) Sensory characteristics**
+
+Sensory characteristics refer to deterioration in vision, hearing, and tactile perception. Visual impairments may hinder recognition of small or low-contrast text; hearing loss can reduce comprehension of audio cues; and diminished tactile sensitivity can weaken haptic feedback.
+
+Therefore, it is recommended that interfaces consider the following:
+
+- Employ high-contrast colours and large fonts.
+- Offer multimodal feedback combining auditory, visual, and tactile signals.
+- Support alternative sensory channels to compensate for deficits.
+
+#### **4) Psychological and emotional characteristics**
+
+Psychological and emotional characteristics include experiences of loneliness, anxiety, social isolation, and the need for emotional support. Emotional well-being and social connection greatly affect user engagement.
+
+Therefore, it is recommended that interfaces consider the following:
+
+- Incorporate empathetic interaction designs.
+- Provide positive reinforcement and encouragement.
+
+- Facilitate friendly and natural conversational elements to build emotional rapport.
+
+#### 5) Environmental characteristics
+
+Environmental characteristics relate to the user's physical, cultural, and linguistic context. Factors such as lighting, ambient noise, temperature, and device placement affect accessibility. Additionally, language comprehension and cultural symbolism influence user acceptance.
+
+Therefore, it is recommended that interfaces consider the following:
+
+- Adapt screen brightness according to ambient lighting conditions.
+- Employ robust voice recognition capable of functioning in noisy environments.
+- Support ergonomically optimized input methods.
+- Use clear, culturally appropriate language and provide multilingual or dialect options.
+
+### 7.2 Intelligent user interface features for persons with age-related disabilities
+
+It is recommended intelligent user interfaces (IUIs) be designed for persons with age-related disabilities to reflect age-related characteristics and diverse user needs.
+
+The key features are as follows:
+
+- Enhanced accessibility:
+ - To accommodate physical and sensory limitations, IUIs provide voice commands, gesture recognition, large displays, and high-contrast user interfaces. Contactless control methods improve ease of use.
+- Cognitive assistance:
+ - To reduce memory decline and cognitive load, IUIs offer step-by-step guidance, intuitive menu structures, clear feedback, and notifications. They also support personalized information delivery and repetitive learning.
+- Multimodal interaction:
+ - IUIs support interaction through multiple sensory channels such as visual, auditory, and tactile pathways, enabling communication tailored to individual sensory capabilities.
+- Emotional empathy and support:
+ - To promote emotional stability and social connectedness, IUIs incorporate friendly conversation, positive reinforcement, emotion recognition, and appropriate responses, helping to alleviate loneliness and anxiety.
+- Context and environmental adaptability:
+ - IUIs actively adapt to environmental changes by adjusting screen brightness, improving voice recognition in noisy settings, and providing personalized services based on user context.
+- Personalization and customization:
+ - IUIs automatically adjust interfaces and services based on users' health status, preferences, and usage patterns, delivering personalized experiences.
+- Continuous learning and feedback:
+ - AI-based systems analyse and learn from user behaviour to continuously improve the interface, providing useful feedback and support.
+
+### 7.3 Service models for persons with age-related disabilities
+
+This clause presents four representative service models based on IUI technologies that reflect the characteristics and needs of persons with age-related disabilities.
+
+A smart healthcare service using AI and a speech recognition interface is illustrated in Figure 1.
+
+- Service model: AI-based care system for persons with age-related disabilities.
+- Scope: Real-time monitoring of cognitive and health status and the provision of personalized care services through AI.
+- Actors:
+ - User: Persons with age-related disabilities, family members and caregivers.
+ - System: AI care system.
+- Preconditions: Persons with age-related disabilities wear sensors and wearable devices, and the AI system is operating normally.
+- Basic Flow:
+ - Sensors and input devices collect biometric signals, sleep conditions, health status, medication adherence, and overall well-being data from persons with age-related disabilities.
+ - The AI and speech recognition interface analyse the collected voice and biometric data to provide appropriate responses based on the user's condition and detect any unusual circumstances compared to normal daily patterns.
+ - Upon detecting anomalies, the AI sends real-time automated messages to caregivers to enable prompt intervention.
+ - Personalized health management, notifications, and care actions are provided, with status alerts and feedback communicated to caregivers and family members.
+- Postconditions: Maintenance of health status and early risk response for persons with age-related disabilities.
+- Special Requirements: It is recommended that AI adjust the intensity and frequency of notifications considering the cognitive decline characteristics of persons with age-related disabilities.
+
+
+
+The diagram illustrates the flow of data and interaction within an 'Elder care system'. On the left, 'Persons with age related disabilities' provide 'Input (User voice)' via a 'Phone call ....'. This input is processed by the 'Elder care system', which contains 'Speech-to-text file' and 'Data storage' components. The data is then sent to 'Analysing data', which in turn connects to an 'AI-based online platform'. From this platform, there are two outputs: 'Output (Text-to-speech)' represented by a speaker icon, and 'Output (Report)' which is sent to a 'Caregiver' represented by three person icons. The reference code 'F.746.21(25)' is shown at the bottom right.
+
+Diagram of the Elder care system for persons with age-related disabilities using AI.
+
+**Figure 1 – Care system for persons with age-related disabilities using AI**
+
+A counselling service model based on artificial emotional intelligence (AEI) technologies is illustrated in Figure 2.
+
+- Service model: AI-based counselling service.
+- Scope: AI counselling service for emotional stability and psychological support for persons with age-related disabilities.
+
+- Actors:
+ - User: Persons with age-related disabilities, family member and, psychological experts.
+ - System: AI counselling system.
+- Preconditions: Persons with age-related disabilities have access to the AI counselling service.
+- Basic Flow:
+ - The AI counselling service integrates AEI technologies, including emotional recognition, generation, and augmentation, to analyse the emotional state of persons with age-related disabilities.
+ - By learning through AI algorithms, it provides personalized emotional support solutions based on comprehensive analysis of human faces, voices, and gestures.
+ - The service offers advice on appropriate behaviour in various situations such as interviews and supports communication and relationship improvement by identifying emotional relationship characteristics in interactions with others.
+ - It enhances emotional and psychological stability by understanding emotional states through biometric information, facial expressions, images, or voice.
+- Postconditions: Enhanced emotional stability and psychological support for persons with age-related disabilities.
+- Special requirements: It is recommended that the AI counsellor accurately recognize persons with age-related disabilities' language patterns and emotional changes.
+- Notes: AI counselling services play a vital role in improving emotional health and strengthening social bonds among persons with age-related disabilities.
+
+
+
+Conceptual diagram of a counselling service using AEI. The diagram shows five input modalities on the left: Facial expression (represented by an eye icon), Acoustic features of voice (represented by a waveform), Gesture (represented by four human figures), Dialogue (represented by a speech bubble with 't e x t'), and an unlabeled icon of a person with a question mark. Arrows from these inputs point to a central 'Machine learning' node, which is depicted as a neural network diagram. From this node, an arrow points to a vertical stack of seven emotion icons: Happy, Sad, Angry, Shocked, Neutral, Excited, and Relaxed. Below this stack is the label 'Emotion' and the code 'F.746.21(25)'. An arrow from the emotion icons points to the text 'Counselling service based on emotional intent'.
+
+**Figure 2 – Conceptual diagram of a counselling service using AEI [b-ITU-T H.862.6]**
+
+An AI speaker service employing a voice user interface (VUI) to respond to user commands is illustrated in Figure 3.
+
+- Service model: Proactive AI speaker-based interface for persons with age-related disabilities.
+- Scope:
+ - An AI speaker with IUI services recognizes commands from persons with age-related disabilities and delivers contextually appropriate information with emotionally adaptive responses.
+
+- Through natural language processing and speech recognition, the system provides personalized information and enables interactive communication tailored to the needs of users.
+- Actors:
+ - User: Persons with age-related disabilities.
+ - System: AI speaker integrated with IUI services.
+- Preconditions: Persons with age-related disabilities are able to interact with the AI speaker through voice.
+- Basic Flow:
+ - The user issues a command using natural language without requiring prior training (intuitiveness and accessibility).
+ - The AI speaker converts the spoken command into text and matches it with its internal command database (AI and machine learning integration).
+ - If the command is unclear or ambiguous, the system requests additional clarification from the user (continuous support and feedback).
+ - Based on the user's response, the system provides appropriate information or performs the requested action (personalization and customization).
+ - Information is delivered through voice along with visual feedback such as holograms (multimodal interaction).
+ - The system expresses emotions through voice tone or manner of speaking, enabling a human-like interaction experience (user-friendliness, emotional expression).
+ - The system learns from interactions to continuously improve the relevance and accuracy of future communications (AI and machine learning integration, continuous support).
+- Postconditions: Enhanced convenience and quality of daily life for persons with age-related disabilities.
+- Special Requirements: It is recommended that the AI incorporate the pronunciation characteristics of persons with age-related disabilities to improve speech recognition accuracy. Additionally, the user interface (UI) response time should be adjusted to accommodate the interaction pace typical of users.
+
+
+
+```
+
+graph TD
+ Input[Input User voice] --> RVF[Recording voice files]
+ subgraph CentralUnit [Voice files and network communication control sensor and output control]
+ RVF
+ STTF[Speech-to-text file]
+ OC[Output control]
+ end
+ RVF --> SAT[Speech API Speech-to-text]
+ SAT --> CUIS[Conversational user interface server]
+ CUIS --> SSA[Speech synthesis API]
+ SSA --> STTF
+ SSA --> OC
+ OC --> OTS[Output Text-to-speech]
+ OTS --> HLC[Hologram LED control]
+ subgraph HLC [Hologram LED control]
+ MCB[Motor control board]
+ Motor[Motor]
+ end
+ CentralUnit --> THIS[Temperature, humidity, illumination Sensor]
+ THIS --> THD[Temperature, humidity, illumination Database]
+ THD --> DVS[Database value charting Server]
+ DVS --> UMM[User movement monitoring]
+ F7462125[F.746.21(25)]
+
+```
+
+Figure 3: AI speaker of active interaction tailored to persons with age-related disabilities. The diagram shows a flow from 'Input (User voice)' to a 'Recording voice files' block, which is part of a larger 'Voice files and network communication control sensor and output control' unit. This unit connects to a 'Speech API (Speech-to-text)' and a 'Speech synthesis API', both of which are connected to a 'Conversational user interface server'. The 'Speech synthesis API' also connects to a 'Speech-to-text file' and an 'Output control' block within the central unit. The 'Output control' block connects to an 'Output (Text-to-speech)' block, which in turn connects to a 'Hologram LED control' unit containing a 'Motor control board' and a 'Motor'. The 'Voice files and network communication control sensor and output control' unit also connects to a 'Temperature, humidity, illumination Sensor', which connects to a 'Temperature, humidity, illumination Database', which then connects to a 'Database value charting Server', which finally connects to a 'User movement monitoring' block. The reference code F.746.21(25) is shown at the bottom right.
+
+**Figure 3 – AI speaker of active interaction tailored to persons with age-related disabilities**
+
+A smart health services using speech recognition interface illustrated in Figure 4.
+
+- Service model: Smart health service based on a speech recognition interface.
+- Scope: This service model defines a smart health service that leverages a speech recognition-based user interface (SUI) to detect the voice and emergency situations of persons with age-related disabilities, initiate interaction, and automatically request assistance when necessary.
+- Actors:
+ - User: Persons with age-related disabilities.
+ - System: Smart health system based on a speech recognition interface (including a smart speaker).
+- Preconditions: The user is within range of a device equipped with a microphone; the system has active speech recognition and a registered emergency contact.
+- Basic Flow:
+ - The system receives and analyses voice input through embedded sensors (intuitiveness and accessibility).
+ - Speech recognition algorithms detect abnormal patterns or emergency indicators (AI and machine learning integration).
+ - If an emergency is suspected, the system attempts to initiate a conversation with the user (continuous support and feedback).
+ - If no response is received, the system sends an alert to the emergency contact system (safety, compatibility).
+ - The user's health status and emergency information are forwarded to the relevant medical institution (multimodal interaction, compatibility).
+ - The service is deployed through the smart speaker interface and can be easily implemented in existing devices (user-friendliness, compatibility).
+- Postconditions: Enhancement of healthcare accessibility and timely response to emergencies.
+
+- Special Requirements:
+ - It is recommended that customized recognition models be trained on the speech and emergency vocal cues of persons with age-related disabilities.
+ - Local processing or encryption technologies should be applied to ensure privacy protection.
+ - A highly responsive interface is required to avoid misdetection and ensure seamless interaction.
+
+
+
+The diagram illustrates the care services for persons with age-related disabilities based on a speech recognition interface. It consists of several interconnected components:
+
+- Sensor based emergency detection** leads to **Active speech recognition to identify situation**, which leads to **Real-time speech recognition and response**, which leads to **Emergency rescue contact system**.
+- Below the flow, three potential events are shown: **Heart attack** (represented by a heart with a red cross), **Fall** (represented by a person falling), and **Stroke** (represented by a brain with a yellow starburst). A red line graph labeled **Event occurred** is shown below these events.
+- An arrow from the **Real-time speech recognition and response** box points to a box containing an icon of a person with a cane and the text **Determine location**. This arrow is labeled **Conversation is not possible**.
+- An arrow from the **Determine location** box points to a box containing two icons: a red cross and a star. This arrow is labeled **Conversation system activated (Health status feedback, emergency connections)**.
+- The final box is labeled **Emergency connection**.
+- The text **F.746.21(25)** is shown in the bottom right corner.
+
+Figure 4: Care services for persons with age-related disabilities based on speech recognition interface. The diagram illustrates a flow from sensor-based detection to emergency response. It shows three potential events (Heart attack, Fall, Stroke) leading to a state where conversation is not possible. This triggers a conversation system activation (health status feedback, emergency connections) which then leads to an emergency connection (represented by a red cross and a star icon). A red line graph labeled 'Event occurred' is shown below the events.
+
+**Figure 4 – Care services for persons with age-related disabilities based on speech recognition interface**
+
+## 8 Conceptual model of IUI for persons with age-related disabilities care systems
+
+This clause describes the conceptual model of IUI in care systems for persons with age-related disabilities. The model aims to define the data flows and interaction flows among hardware components, software services, and intelligent systems that facilitate personalized, adaptive, and safe user experiences.
+
+The input and output data are multimodal and incorporate various modalities such as speech, text, video, facial expressions, and gestures for both user interaction and system response. In some intelligent care systems for persons with age-related disabilities, the emotional content of the input data serves as a critical parameter for system functions and personalized service delivery.
+
+### 8.1 Components of the conceptual model
+
+The IUI system consists of the following main components:
+
+- User: Persons with age-related disabilities.
+- HW:
+ - Input devices: Microphone (speech), camera or depth sensor (video, facial expression, gesture).
+
+- Output devices: Speaker (for speech), display/projector (for facial animation or visual cues).
+- Embedded systems: Edge computing processors for low-latency processing.
+- SW:
+ - Software that processes multimodal inputs to extract meaning and emotion.
+- AI/ML:
+ - Algorithms that analyse user data, detect changes in cognitive or physical states, and adapt the UI accordingly for personalization and continuous support.
+- External service interfaces.
+ - Integration points for healthcare, emergency response, and other support services to enhance safety and provide timely assistance.
+
+### 8.2 Input and output module
+
+This module is responsible for input and output processing functions within the IUI system, focusing on the integrated analysis of multimodal signals and the provision of personalized feedback.
+
+- **Input:** Multimodal signals (e.g., voice, gesture, biosignals) are received through sensors or user input devices.
+- **Processing:** AI models analyse intent, context, and emotional state, referencing personalization settings.
+- **Output:** The system provides appropriate feedback (e.g., voice, visual cues, ambient signals) tailored to the user's needs.
+- **Feedback:** User responses and system logs are used for further tuning and real-time error handling.
+
+Table 1 shows the input and output elements of the IUI service.
+
+**Table 1 – Input and output elements of IUI**
+
+| Category | Element | Description |
+|-------------------|---------------------|----------------------------------------------------------------------------------------------------|
+| Input | Voice | Voice signals captured via microphone |
+| | Gesture | Hand and body movements detected by cameras/sensors |
+| | Biosignals | Physiological signals such as heart rate, electroencephalogram (EEG), galvanic skin response (GSR) |
+| Processing | Intent analysis | AI models for natural language and behaviour recognition |
+| | Context analysis | Interpretation of situational and environmental data |
+| | Emotion recognition | AI algorithms for detecting emotional states |
+| | Personalization | Incorporation of user profile and preferences |
+| Output | Voice feedback | Speech synthesis and voice output |
+| | Visual cues | Visual information displayed on screens or devices |
+| | Ambient signals | Environmental signals such as lighting and vibration |
+| Feedback | User response | Collection of user reactions |
+| | System logs | Logs of errors and usage history |
+| | Real-time tuning | Real-time adjustment of AI models based on feedback |
+
+### 8.3 Data and interaction flow
+
+The interaction process within the conceptual model consists of the following steps:
+
+- **Data collection:** Sensors and input devices collect user activity, physiological signals, and environmental context.
+- **Analysis:** AI/ML algorithms process the collected data to detect cognitive or physical changes, usage patterns, and potential risks.
+- **Adaptation:** Based on the analysis results, the UI dynamically adapts to simplify navigation, adjust input methods, and customize feedback.
+- **Feedback:** Continuous support is provided through alerts, assistance, or adjustments, enhancing user confidence and safety.
+- **User interaction:** The user interacts through multimodal inputs (voice, touch, gesture), with the system responding in an intuitive and accessible manner.
+
+Table 2 shows data flow and interaction processes in the IUI system.
+
+**Table 2 – Data flow and interaction processes in the IUI system**
+
+| From → To | Description |
+|---------------------------|-----------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+| User → Input devices | Users provide input via voice, touch, motion and other modalities. |
+| Input devices → AI/ML | Collected data are analysed by AI. |
+| AI/ML → Software | The UI is customized for the user. |
+| Software → User | Adaptive UI feedback is provided (e.g., screen, voice, feedback). |
+| AI/ML ↔ External services | Integration with external services such as health information and emergency response.
External service data are exchanged with AI/ML for enhanced personalization. |
+
+### 8.4 Conceptual model diagram
+
+The conceptual model includes a bidirectional interaction flow between persons with age-related disabilities and the IUI system.
+
+Input modalities such as voice, touch, and environmental sensors provide real-time data to the processing unit of the system. These data are interpreted by AI/ML models and delivered through multimodal output formats such as visual cues, voice feedback, and tactile responses. These input and output layers are essential for ensuring the intuitiveness, accessibility, and real-time responsiveness of IUI services.
+
+Figure 5 illustrates the conceptual model diagram of the IUI system.
+
+
+
+```
+
+graph TD
+ A["Person with age-related disabilities
+(Age-related needs)"] -- "Input: Voice, gesture, biosignals" --> B["Input collection
+(Sensor, camera, mic, UI devices)"]
+ B --> C["AI/ML processing unit
+- Emotion recognition
+- Intent prediction
+- Personalization logic"]
+ C --> D["Output module
+- Voice feedback
+- Visual display
+- Haptic or ambient signals"]
+ D --> E["Monitoring and feedback loop
+- User satisfaction
+- Error handling
+- Learning from interaction"]
+
+```
+
+F.746.21(25)
+
+Flowchart of the conceptual model of IUI for care systems for persons with age-related disabilities. The flow consists of five rectangular boxes connected by downward-pointing arrows. The first box is 'Person with age-related disabilities (Age-related needs)'. The second box is 'Input collection (Sensor, camera, mic, UI devices)' with the text 'Input: Voice, gesture, biosignals' above it. The third box is 'AI/ML processing unit' with sub-points: '- Emotion recognition', '- Intent prediction', and '- Personalization logic'. The fourth box is 'Output module' with sub-points: '- Voice feedback', '- Visual display', and '- Haptic or ambient signals'. The fifth box is 'Monitoring and feedback loop' with sub-points: '- User satisfaction', '- Error handling', and '- Learning from interaction'. A small code 'F.746.21(25)' is at the bottom right of the diagram.
+
+**Figure 5 – Conceptual model of IUI for care systems for persons with age-related disabilities**
+
+## 9 Requirements for common components and characteristics of the intelligent UI service
+
+This clause defines the common components and characteristics that form the foundation of IUI services for persons with age-related disabilities. These elements ensure consistency, interoperability, and usability across various service scenarios.
+
+### 9.1 Requirements for common components
+
+Common components include:
+
+- User profile and context manager:
+ - It is recommended to maintain demographic information, cognitive and sensory abilities, and user preferences of persons with age-related disabilities.
+ - It is recommended to update the profile dynamically according to usage history and real-time conditions.
+- Multimodal input processing units:
+ - It is recommended to integrate data collected through voice, gestures, and biosignals.
+ - It is recommended to perform synchronization and fusion of multimodal data.
+- AI/ML analysis engine:
+ - It is recommended to execute intent recognition, context analysis, and emotion detection.
+
+- It is recommended to adaptively adjust service parameters to provide personalized services.
+- Interaction management module:
+ - It is recommended to control the flow of user interaction to support smooth dialogue and task execution.
+ - It is recommended to maintain a balance between automation and user control.
+- Multimodal output generator:
+ - It is recommended to provide information through voice, visual, and ambient feedback channels.
+ - It is recommended to adjust output methods according to the user's sensory characteristics.
+- Feedback and learning loop:
+ - It is recommended to collect system usage logs and user responses.
+ - It is recommended to support long-term personalization and improve service quality.
+- External service interface:
+ - It is recommended to connect with healthcare systems, caregivers, and emergency response services.
+ - It is recommended to ensure interoperability with existing information and communication technology (ICT) and Internet of things (IoT) platforms.
+
+### 9.2 Requirements for common characteristics
+
+IUI services for persons with age-related disabilities share several common characteristics that support usability, accessibility, and trust. These characteristics describe how the services should behave and respond across different applications.
+
+- Accessibility and inclusiveness:
+ - It is recommended to design interfaces to be easily used by persons with age-related disabilities with different physical, cognitive, and sensory abilities.
+- Adaptability and personalization:
+ - It is recommended to allow customization of font size, colour, voice speed, and interaction pace.
+- Multimodality:
+ - It is recommended to support multiple input and output channels such as voice, text, gesture, and vibration.
+ - It is recommended to provide redundant communication paths (e.g., both audio and visual) to reduce the risk of misunderstanding.
+- Empathy and emotional responsiveness:
+ - It is recommended to include empathetic interaction methods such as friendly voice, positive feedback, and natural conversation.
+- Reliability and trustworthiness:
+ - It is recommended to ensure the system is stable, safe, and consistent in its operation.
+- Interoperability:
+ - It is recommended to support compatibility with different devices, platforms, and external services such as healthcare or emergency systems.
+
+- Continuous improvement:
+ - It is recommended to collect feedback and usage data to improve the service over time.
+ - It is recommended to apply AI/ML learning techniques to adapt the interface as user needs evolve.
+
+## **10 Intelligent UI service requirements from a hardware perspective**
+
+IUI hardware requirements are required to consider the physical, cognitive, and sensory characteristics of persons with age-related disabilities. The requirements cover input devices, output devices, ergonomic design, and connectivity.
+
+- Input devices
+ - Input devices are required to support various input methods such as touch, voice, gesture, and physical buttons.
+ - Input devices are recommended to be designed with a large size and wide spacing to minimize erroneous operations.
+ - Input devices are recommended to provide immediate feedback (e.g., vibration, audio, visual indication) to user actions.
+- Output devices
+ - Displays are required to support large fonts, high contrast, and wide viewing angles.
+ - Output devices are recommended to provide adjustable sound output and caption functions for users with hearing impairments.
+ - Tactile feedback (e.g., vibration, Braille) is recommended to be provided as a complementary channel.
+ - Emergency alerts are required to provide simultaneous visual, auditory, and tactile signals.
+- Ergonomic design
+ - Devices are recommended to be lightweight and designed to minimize burden for persons with age-related disabilities during long-term use.
+ - Devices are recommended to be designed with consideration of the hand size, muscular strength, and reaction speed of persons with age-related disabilities.
+- Connectivity and interoperability
+ - Devices are recommended to support wireless communication such as Bluetooth, Wi-Fi, and NFC.
+ - Devices are recommended to ensure interoperability with smart home and healthcare devices.
+
+## **11 Intelligent UI service requirements from a software perspective**
+
+- User interface:
+ - UI is recommended to minimize the number of steps required to access core functions.
+ - UI is recommended to be designed so that users can adjust font size, colour contrast, and language expressions.
+ - UI is recommended to maintain consistent menu structures and icon design.
+- Accessibility:
+ - Software is recommended to support voice interfaces optimized for the speech characteristics of persons with age-related disabilities.
+
+- It is recommended to utilize the multimodal feedback functions of hardware output devices to provide combined interaction through visual, auditory, and tactile channels.
+
+- User experience:
+ - Software is recommended to provide tutorials, step-by-step guidance, and voice assistance to improve learnability.
+ - It is recommended that software encrypt sensitive information (e.g., health, location, financial data) for storage and transmission.
+
+Error messages are recommended to be expressed in simple and intuitive language.
+
+- Security and privacy:
+ - Software is recommended to encrypt sensitive information (e.g., health, location, financial data).
+ - Software is recommended to provide functions that allow caregivers and family members to remotely manage the system with limited authority.
+- Intelligent features:
+ - Software is recommended to provide multimodal notifications (visual, auditory, tactile) for medication, schedules, and emergency situations.
+ - Software is recommended to learn user habits and provide personalized function recommendations.
+
+## Bibliography
+
+- [b-ITU-T F.791] Recommendation ITU-T F.791 (2018), *Accessibility terms and definitions*.
+- [b-ITU-T F.902] Recommendation ITU-T F.902 (1995), *Interactive services design guidelines*.
+- [b-ITU-T H.862.6] Recommendation ITU-T H.862.6 (2023), *Functional requirements for counselling services based on artificial emotional intelligence*.
+- [b-ITU-T Y.3172] Recommendation ITU-T Y.3172 (2019), *Architectural framework for machine learning in future networks including IMT-2020*.
+- [b-ETSI GR ENI 004] ETSI GR ENI 004 V1.1.1 (2018), *Experiential Networked Intelligence (ENI); Terminology for Main Concepts in ENI*.
+
+
+
+## SERIES OF ITU-T RECOMMENDATIONS
+
+| | |
+|-----------------|-----------------------------------------------------------------------------------------------------------------------------------------------------------|
+| Series A | Organization of the work of ITU-T |
+| Series D | Tariff and accounting principles and international telecommunication/ICT economic and policy issues |
+| Series E | Overall network operation, telephone service, service operation and human factors |
+| Series F | Non-telephone telecommunication services |
+| Series G | Transmission systems and media, digital systems and networks |
+| Series H | Audiovisual and multimedia systems |
+| Series I | Integrated services digital network |
+| Series J | Cable networks and transmission of television, sound programme and other multimedia signals |
+| Series K | Protection against interference |
+| Series L | Environment and ICTs, climate change, e-waste, energy efficiency; construction, installation and protection of cables and other elements of outside plant |
+| Series M | Telecommunication management, including TMN and network maintenance |
+| Series N | Maintenance: international sound programme and television transmission circuits |
+| Series O | Specifications of measuring equipment |
+| Series P | Telephone transmission quality, telephone installations, local line networks |
+| Series Q | Switching and signalling, and associated measurements and tests |
+| Series R | Telegraph transmission |
+| Series S | Telegraph services terminal equipment |
+| Series T | Terminals for telematic services |
+| Series U | Telegraph switching |
+| Series V | Data communication over the telephone network |
+| Series X | Data networks, open system communications and security |
+| Series Y | Global information infrastructure, Internet protocol aspects, next-generation networks, Internet of Things and smart cities |
+| Series Z | Languages and general software aspects for telecommunication systems |
\ No newline at end of file
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+
+
+International Telecommunication Union
+
+**ITU-T**
+
+TELECOMMUNICATION
+STANDARDIZATION SECTOR
+OF ITU
+
+**F.746.3**
+
+(11/2015)
+
+SERIES F: NON-TELEPHONE TELECOMMUNICATION
+SERVICES
+
+Audiovisual services
+
+---
+
+**Intelligent question answering service
+framework**
+
+Recommendation ITU-T F.746.3
+
+
+
+The logo of the International Telecommunication Union (ITU) is located in the bottom right corner. It features a stylized globe with a red lightning bolt striking across it. To the right of the globe, the text "ITU" is written in a bold, blue font, and below it, "International Telecommunication Union" is written in a smaller, blue font.
+
+ITU logo: A globe with a red lightning bolt and the text 'ITU International Telecommunication Union'.
+
+# ITU-T F-SERIES RECOMMENDATIONS **NON-TELEPHONE TELECOMMUNICATION SERVICES**
+
+| | |
+|-----------------------------------------------------------------|--------------------|
+| TELEGRAPH SERVICE | |
+| Operating methods for the international public telegram service | F.1–F.19 |
+| The gentex network | F.20–F.29 |
+| Message switching | F.30–F.39 |
+| The international telemessage service | F.40–F.58 |
+| The international telex service | F.59–F.89 |
+| Statistics and publications on international telegraph services | F.90–F.99 |
+| Scheduled and leased communication services | F.100–F.104 |
+| Phototelegraph service | F.105–F.109 |
+| MOBILE SERVICE | |
+| Mobile services and multdestination satellite services | F.110–F.159 |
+| TELEMATIC SERVICES | |
+| Public facsimile service | F.160–F.199 |
+| Teletex service | F.200–F.299 |
+| Videotex service | F.300–F.349 |
+| General provisions for telematic services | F.350–F.399 |
+| MESSAGE HANDLING SERVICES | F.400–F.499 |
+| DIRECTORY SERVICES | F.500–F.549 |
+| DOCUMENT COMMUNICATION | |
+| Document communication | F.550–F.579 |
+| Programming communication interfaces | F.580–F.599 |
+| DATA TRANSMISSION SERVICES | F.600–F.699 |
+| AUDIOVISUAL SERVICES | F.700–F.799 |
+| ISDN SERVICES | F.800–F.849 |
+| UNIVERSAL PERSONAL TELECOMMUNICATION | F.850–F.899 |
+| HUMAN FACTORS | F.900–F.999 |
+
+*For further details, please refer to the list of ITU-T Recommendations.*
+
+# Recommendation ITU-T F.746.3
+
+# Intelligent question answering service framework
+
+## Summary
+
+Recommendation ITU-T F.746.3 defines the intelligent question answering service (IQAS) framework as well as the features, requirements and the functionality to support the intelligent question answering (QA) service. The intelligent QA system is an advanced function to generate answers to a user's questions in a natural language. More and more systems in the future are expected to be equipped with QA functions for an advanced user experience.
+
+## History
+
+| Edition | Recommendation | Approval | Study Group | Unique ID* |
+|---------|----------------|------------|-------------|---------------------------------------------------------------------------|
+| 1.0 | ITU-T F.746.3 | 2015-11-29 | 16 | 11.1002/1000/12619 |
+
+## Keywords
+
+Intelligent system, natural language processing, QA, question answering.
+
+---
+
+\* To access the Recommendation, type the URL in the address field of your web browser, followed by the Recommendation's unique ID. For example, .
+
+## FOREWORD
+
+The International Telecommunication Union (ITU) is the United Nations specialized agency in the field of telecommunications, information and communication technologies (ICTs). The ITU Telecommunication Standardization Sector (ITU-T) is a permanent organ of ITU. ITU-T is responsible for studying technical, operating and tariff questions and issuing Recommendations on them with a view to standardizing telecommunications on a worldwide basis.
+
+The World Telecommunication Standardization Assembly (WTSA), which meets every four years, establishes the topics for study by the ITU-T study groups which, in turn, produce Recommendations on these topics.
+
+The approval of ITU-T Recommendations is covered by the procedure laid down in WTSA Resolution 1.
+
+In some areas of information technology which fall within ITU-T's purview, the necessary standards are prepared on a collaborative basis with ISO and IEC.
+
+## NOTE
+
+In this Recommendation, the expression "Administration" is used for conciseness to indicate both a telecommunication administration and a recognized operating agency.
+
+Compliance with this Recommendation is voluntary. However, the Recommendation may contain certain mandatory provisions (to ensure, e.g., interoperability or applicability) and compliance with the Recommendation is achieved when all of these mandatory provisions are met. The words "shall" or some other obligatory language such as "must" and the negative equivalents are used to express requirements. The use of such words does not suggest that compliance with the Recommendation is required of any party.
+
+## INTELLECTUAL PROPERTY RIGHTS
+
+ITU draws attention to the possibility that the practice or implementation of this Recommendation may involve the use of a claimed Intellectual Property Right. ITU takes no position concerning the evidence, validity or applicability of claimed Intellectual Property Rights, whether asserted by ITU members or others outside of the Recommendation development process.
+
+As of the date of approval of this Recommendation, ITU had received notice of intellectual property, protected by patents, which may be required to implement this Recommendation. However, implementers are cautioned that this may not represent the latest information and are therefore strongly urged to consult the TSB patent database at .
+
+© ITU 2016
+
+All rights reserved. No part of this publication may be reproduced, by any means whatsoever, without the prior written permission of ITU.
+
+## Table of Contents
+
+| | Page |
+|--------------------------------------------------------------------------------------------------------------------|------|
+| 1 Scope..... | 1 |
+| 2 References..... | 1 |
+| 3 Definitions ..... | 1 |
+| 3.1 Terms defined elsewhere ..... | 1 |
+| 3.2 Terms defined in this Recommendation..... | 1 |
+| 4 Abbreviations and acronyms ..... | 2 |
+| 5 Conventions ..... | 3 |
+| 6 Introduction..... | 3 |
+| 7 Requirements ..... | 4 |
+| 7.1 General requirements for intelligent question answering service and the system to support the QA service ..... | 4 |
+| 7.2 Natural language processing requirements..... | 5 |
+| 7.3 Question analysis requirements ..... | 5 |
+| 7.4 Candidate answer generation requirements..... | 6 |
+| 7.5 Answer inference and generation requirements ..... | 6 |
+| 8 Functional components and interfaces for intelligent question answering service ..... | 7 |
+| 8.1 Natural language processing..... | 7 |
+| 8.2 Question analysis..... | 9 |
+| 8.3 Candidate answer generation..... | 11 |
+| 8.4 Answer inference and generation ..... | 12 |
+| Bibliography..... | 13 |
+
+
+
+# Recommendation ITU-T F.746.3
+
+## Intelligent question answering service framework
+
+# 1 Scope
+
+This Recommendation provides an overview of the intelligent question answering service (IQAS) framework and describes the features, general requirements and functionality which form a framework to support the intelligent question answering (QA) service. The scope of this Recommendation focuses on QA architecture, devices, servers, interfaces and communication protocols among QA servers and clients in a high-level approach.
+
+# 2 References
+
+None.
+
+# 3 Definitions
+
+## 3.1 Terms defined elsewhere
+
+This Recommendation uses the following terms defined elsewhere:
+
+**3.1.1 application** [b-ITU-T Y.101]: A structured set of capabilities, which provide value-added functionality supported by one or more services.
+
+**3.1.2 content** [b-ITU-T H.780]: A combination of audio, still image, graphic, video, or data.
+
+NOTE – Variety of formats is classified as the "data" (e.g., text, encoded values, multimedia description language introduced by [b-ITU-T H.760]).
+
+## 3.2 Terms defined in this Recommendation
+
+This Recommendation defines the following terms:
+
+**3.2.1 co-reference resolution**: A function that detects the preceding referents of the pronouns which replace the noun phrases of the input sentences.
+
+**3.2.2 CV\_occupation**: A named entity tag that belongs to the civilization (CV) category that indicates a person's occupation (e.g., scientist).
+
+**3.2.3 CV\_prize**: A named entity tag that belongs to the civilization (CV) category that indicates a prize (e.g., the Nobel prize).
+
+**3.2.4 IsA relation**: A hierarchical relation between two words in such a way that the meaning of one word includes that of the other word.
+
+**3.2.5 knowledge base**: A collection of knowledge resources that consist of structured and unstructured data. The knowledge base is used to provide information to the various applications that are related to information provision such as the QA system and search system.
+
+**3.2.6 named entity recognition**: A function that recognizes named entities such as PLO entities which are people, locations and organizations from the sentences. The PLO can be decomposed into more specific named entities depending on the applications.
+
+**3.2.7 natural language processing**: A method that analyses text in natural languages through several processes such as part-of-speech recognition, syntactic analysis and semantic analysis.
+
+**3.2.8 part-of-speech recognition**: A function that recognizes parts of speech (POS) in the sentences and assigns relevant POS tags considering contextual meaning of the target sentences.
+
+**3.2.9 question answering:** A system that provides answers in natural language to questions which are in natural language form by analysing the questions and all the knowledge resources that are available to the system.
+
+**3.2.10 semantic analysis:** A function that recognizes the semantic relations among the words around predicates that exist in the same sentence. The semantic analysis function then generates a semantic predicate-argument structure (PAS).
+
+**3.2.11 syntactic analysis:** A function that analyses sentence structures and generates dependency relations among words based on dependency grammars.
+
+# **4 Abbreviations and acronyms**
+
+This Recommendation uses the following abbreviations and acronyms:
+
+| | |
+|--------|----------------------------------------|
+| ARG | Argument |
+| CV | Civilization |
+| DB | Database |
+| DS | Digital Signage |
+| ID | Identifier |
+| IQAS | Intelligent Question Answering Service |
+| KB | Knowledge Base |
+| NLP | Natural Language Processing |
+| NLU | Natural Language Understanding |
+| NNG | Noun General |
+| NNP | Proper Noun |
+| NP_OBJ | Noun Phrase Objective |
+| NP_SBJ | Noun Phrase Subjective |
+| PAS | Predicate-Argument Structure |
+| PLO | People, Locations and Organizations |
+| POS | Parts Of Speech |
+| QA | Question Answering |
+| SL | Sub Language |
+| SPARQL | SPARQL protocol and RDF Query Language |
+| SQL | Structured Query Language |
+| VP_MOD | Verb Phrase Modal |
+| VV | Verb |
+| XSNG | Auxiliary Suffix from Noun General |
+| XSV | Auxiliary Suffix from Verb |
+
+# 5 Conventions
+
+The following conventions are used in this Recommendation:
+
+- The keywords "is required to" indicate a requirement which must be strictly followed and from which no deviation is permitted, if conformance to this Recommendation is to be claimed.
+- The keywords "is prohibited from" indicate a requirement which must be strictly followed and from which no deviation is permitted, if conformance to this Recommendation is to be claimed.
+- The keywords "is recommended" indicate a requirement which is recommended but which is not absolutely required. Thus, this requirement need not be present to claim conformance.
+- The keywords "is not recommended" indicate a requirement which is not recommended but which is not specifically prohibited. Thus, conformance with this Recommendation can still be claimed even if this requirement is present.
+- The keywords "can optionally" indicate an optional requirement which is permissible, without implying any sense of being recommended. This term is not intended to imply that the vendor's implementation must provide the option and the feature can be optionally enabled by the network operator/service provider. Rather, it means the vendor may optionally provide the feature and still claim conformance with this Recommendation.
+
+# 6 Introduction
+
+The intelligent question answering (QA) system is an advanced function to generate answers to a user's question in a natural language. More and more systems in the future are expected to be equipped with QA functions for an advanced user experience. Currently, the most widely recognized QA system is an intelligent agent which is provided in smart phones. Although not a completely intelligent agent able to answer all questions that users may ask, a QA service would be useful for a defined environment. A QA service would be useful if a standardized QA service framework existed which could be applied to various domains such as TV-related services, digital signage (DS) and e-health services. A QA service would also be useful in terms of accessibility because natural languages are used to request and provide information conveniently with a speech interface. Figure 1 illustrates the concept of a QA system in the DS domain, where a user requests information about shoe stores from the QA system at a shopping mall.
+
+- Scenario of an intelligent question answering service (IQAS) system: An IQAS system at a shopping mall.
+
+Michelle visits a shopping mall in Seattle. There is a DS helper which displays information about the various shops at the mall. It also answers customers' questions about the shops. Michelle wants to buy a pair of shoes and asks the DS helper "Where can I find some nice shoes?" The DS helper answers "Go to the third floor". Michelle goes to the third floor where she can find some shoe stores. The answer can also be shown in text form on the screen or can be provided by speech synthesis in a spoken form according to the needs of the user.
+
+
+
+Figure 1: Digital signage with a QA function: At the mall. The diagram shows a digital signage screen displaying a mall interior. A person is interacting with the screen, asking 'Go to the third floor.' and 'Where can I find some nice shoes?'. Above the screen, a 'QA server' is connected to a series of server icons. The text 'F.746.3(15)\_F01' is visible in the bottom right corner.
+
+**Figure 1 – Digital signage with a QA function: At the mall**
+
+Figure 2 presents an example of functional blocks in QA architecture. The QA system consists of several functional blocks: natural language processing (NLP), question analysis, candidate answer generation, answer inference and answer generation.
+
+
+
+Figure 2: Example of functional blocks in QA architecture. This flowchart illustrates the QA process: Question -> Question analysis (containing Question understanding) -> Question decomposition -> Candidate answer generation (containing Multiple information search) -> Answer inference (containing Confidence calculation) -> Answer generation (containing Best answer generation) -> Answer. A 'Natural language processing' block feeds into Question analysis and Question decomposition. A globe and network icons represent the information sources. The text 'F.746.3(15)\_F02' is visible in the bottom right corner.
+
+**Figure 2 – Example of functional blocks in QA architecture**
+
+# 7 Requirements
+
+## 7.1 General requirements for IQAS and the system to support the QA service
+
+- The IQAS is required to provide answers to the user's various questions considering the user's intention.
+- The IQAS is recommended to provide answers in natural language, whether it is in text or in spoken form depending on the user's environment.
+- The IQAS is recommended to provide answers in natural language from multiple information sources.
+- The IQAS is recommended to provide accessibility for different user needs.
+
+- The IQAS is recommended to provide answers to the user's questions within a proper time span.
+- It is recommended to provide an input editor for the user's question whether it consists of a single sentence or multiple sentences.
+- It is recommended that the user's question is input in voice or text form depending on the user's device.
+- The IQAS is recommended to provide example questions for the user's convenience.
+- The IQAS is recommended to provide a manual on the use of the system for the user.
+- The IQAS is recommended to provide a human intervention mechanism where the reliability of the answer is below a predefined threshold value.
+- The IQAS is recommended to be able to save and update profile information such as the history of users' questions and answers.
+- The IQAS is recommended to be able to provide answers appropriate to the user's level of knowledge.
+
+## 7.2 Natural language processing requirements
+
+The following requirements relate to NLP in an IQAS and the system to support the IQAS:
+
+- The IQAS system is recommended to include a NLP module that analyses natural language sources at a deep level.
+- The NLP module is recommended to include a pre-processing block that filters non-essential text to better understand the text and increase the speed of the IQAS.
+- The NLP module is recommended to include a part of speech processing block that analyses the natural language text and assigns the correct part of speech tag to the output.
+- The NLP module is recommended to include a named entity processing block that analyses the natural language text and assigns the correct named entity tag to the output for language understanding.
+- The NLP module is recommended to include a syntactic analysis processing block that analyses the structure of the natural language sentences to help understand the information sources.
+- The NLP module is recommended to include a semantic analysis processing block that analyses the meaning and the role of each semantic part of the natural language sentences to help understand the information sources.
+- The NLP module is recommended to include a co-reference resolution processing block that relates nouns with the pronouns that refer to the nouns to help understand the information sources.
+- The NLP module is recommended to continuously update all the language analysis results and extract time/location information and semantic relation information among words based on the continuous update for the IQAS.
+
+## 7.3 Question analysis requirements
+
+The following requirements relate to question analysis in an IQAS and the system to support the IQAS:
+
+- The question analysis module is recommended to analyse the user's question and understand the intention of the user.
+- The question analysis module is recommended to process the user's question, whether it comprises of a single sentence, complex clauses or multiple sentences.
+
+- The question analysis module is recommended to find relevant information on the type of candidate answers.
+- The question analysis module is recommended to decide the best strategy to find evidence for the correct answer and to present it to the user.
+- The question analysis module is recommended to include the functions of question classification, answer type recognition, dictionary title recognition, question decomposition and semantic information analysis for the better understanding of the user's question.
+- It is recommended that the question decomposition results be presented as an intermediate analysis result.
+- It is recommended that the final question analysis results be presented to the user.
+- It is recommended that the question paraphrases or question hypotheses which have the same meaning as the user's question be provided with reliability information.
+- The question analysis module is recommended to be able to make inferences on the user's level of knowledge.
+
+## **7.4 Candidate answer generation requirements**
+
+The following requirements relate to candidate answer generation in an IQAS and the system to support the IQAS:
+
+- The candidate answer generation module is recommended to provide related language knowledge that is the basis for answer candidates to the user's question.
+- The candidate answer generation module is recommended to use the existing knowledge bases for the candidate answer generation.
+- The candidate answer generation module is recommended to add new language knowledge increasingly to the existing knowledge bases.
+- The candidate answer generation module is recommended to provide the interface to retrieve taxonomy from the knowledge bases.
+- It is recommended that the candidate answer generation module provides the ranking of the information that it finds.
+- The IQAS system is required to search for the candidate answers from multiple information sources.
+- The IQAS system is recommended to have various indexed databases of all different informal documents
+- The IQAS system, based on the question analysis results, is recommended to provide the search results, answer rankings and weight information extracted from each of the informal indexed databases.
+
+## **7.5 Answer inference and generation requirements**
+
+The following requirements relate to answer inference and generation in an IQAS and the system to support the IQAS:
+
+- The IQAS system is recommended to calculate the reliability score for each candidate answer based on multiple proofs to support the candidate answers.
+- The information sources are recommended to include big data such as web data, Wikipedia and different knowledge bases that are publically available.
+- It is recommended to provide the source of the extracted documents, paragraphs and sentences to be able to confirm the reasons for the searched candidate answers.
+
+- The IQAS system is required to provide the best answers and their ranks to the user from among the candidate answers based on the confidence scores.
+- It is recommended to provide the information on the reliability of the best answer.
+- It is recommended to provide the best answer from among multiple candidate answers.
+- When the answer is presented by real-time answer generation, the documents and paragraphs from which the answer is extracted are recommended to be presented along with the answer.
+- When the answer is presented based on the knowledge base (KB), the information on the KB is recommended to be provided accordingly.
+
+# 8 Functional components and interfaces for intelligent question answering service
+
+IQAS functional components are basically composed of natural language processing, question analysis, candidate answer generation, answer inference and answer generation functional blocks as follows:
+
+- **Natural language processing functional block:** supports natural language processing on the QA server;
+- **Question analysis functional block:** supports question analysis on the terminal;
+- **Candidate answer generation functional block:** supports candidate answer generation by searching information in various databases (DBs);
+- **Answer inference/generation functional block:** supports answer inference based on feature normalization and ranking of candidate answers and best answer generation on the terminal.
+
+Functional blocks of the intelligent question answering service are shown in Figure 3.
+
+
+
+Figure 3 – Logical functional block diagram of an IQAS. The diagram illustrates the flow of information through four main functional blocks: Question analysis, Candidate answer generation, Answer inference/generation, and Natural language processing. The process starts with a 'Question' input to the 'Question analysis' block, which includes 'Question classification', 'User knowledge inference', 'Question decomposition', 'Question intermediate format generation', and 'Question hypothesis generation'. This block feeds into the 'Candidate answer generation' block, which includes 'Real-time information search', 'Real-time candidate answer generation', 'Multi-source candidate answer generation', 'Text based candidate answer generation', and 'KB-based candidate answer generation'. This block feeds into the 'Answer inference/generation' block, which includes 'Type coercion', 'Answer verification', 'Answer constraints', 'Ranking candidate answers', and 'Answer synthesis'. The output of this block is 'Answer reliability, reason', which leads to 'Human intervention' and then to the final 'Answer'. The 'Natural language processing' block, which includes 'POS recognition', 'Named entity recognition', 'Syntactic analysis', 'Semantic analysis', 'Co-reference resolution', 'Time/location information extraction', 'Semantic relation extraction', 'Continuous linguistic knowledge acquisition/extraction', and 'Learning and extraction of linguistic knowledge', is shown below the other blocks and feeds into the 'Candidate answer generation' block. The entire diagram is enclosed in a dashed box, and the label 'F.746.3(15)\_F03' is in the bottom right corner.
+
+Figure 3 – Logical functional block diagram of an IQAS
+
+## 8.1 Natural language processing
+
+The NLP functional block consists of the natural language understanding function and the linguistic knowledge learning and extraction function. The natural language understanding function analyses the user's questions as well as target documents for knowledge extraction using the technologies of semantic level analysis such as semantic entity recognition and co-reference resolution in addition to the well-known parts of speech (POS) recognition, named entity recognition and syntactic analysis for sentence structures. The linguistic knowledge learning and extraction function shown in Figure 4, extracts semantic relations among words and time/location information in the documents and provides the framework to continuously acquire linguistic knowledge and to extend it to deal with new knowledge.
+
+- Natural language understanding function consists of: the POS recognition sub-function, named entity recognition sub-function, syntactic analysis sub-function, semantic entity recognition sub-function and the co-reference resolution sub-function.
+ - Part of speech recognition:
+
+The POS recognition sub-function analyses sentences by tagging POS tags to the minimum semantic unit which has the meaning. The POS analysis technology recognizes parts of speech in the sentences and documents and assigns relevant POS tags considering contextual meaning of the target sentences. The technology to analyse POS includes rule-based methods and statistical recognition methods.
+ - Named entity recognition:
+
+The named entity recognition sub-function recognizes named entities such as people, locations and organizations (PLO) from the sentences. The PLO can be decomposed to more detailed named entities depending on the applications. Both the rule-based method and the statistical method are used to analyse named entities.
+ - Syntactic analysis:
+
+The syntactic analysis sub-function analyses sentence structures that are input to the module and generates dependency relations among words based on dependency grammars. It performs the functions of head-dependant recognition function, labelling of sentence structure for the dependency relations recognized and storing the recognized dependency and labels to the predefined data structures.
+ - Semantic analysis:
+
+The function of the semantic analysis sub-functional block is to recognize the semantic relations among the words around predicates that exist in the same sentence. It then generates the semantic predicate-argument structure (PAS). For the semantic entity recognition, semantic frames, such as FrameNet, are required that define the semantic roles of the arguments for each predicate. Because it is expensive to manually build all of the different frames one by one, it is required to extend and validate the semantic frames automatically based on a large collection of text.
+
+NOTE – FrameNet is a free downloadable lexical database of English that is both human- and machine-readable, based on annotating examples of how words are used in actual texts. More details can be found at [b-FrameNet].
+ - Co-reference resolution:
+
+The function of the co-reference resolution sub-functional block is to detect the preceding referents of the pronouns which replace the noun phrases of the input sentences.
+- Learning and extraction function of linguistic knowledge
+ - Semantic relation extraction:
+
+The function of the semantic relation extraction sub-functional block is to find the IsA relation among two words based on the deep natural language understanding analysis and to extract the word pair of the IsA relation. The extracted pairs of IsA relations are then stored in the pre-defined data structures.
+
+- Time/location information extraction:
+
+The function of the time/location information extraction sub-functional block is to extract the information related with time/location from the sentences and documents that are necessary to generate answers in the QA system. Time information is the relative, absolute, or abstract time expressions that are present in the sentences. The purpose of the function is to extract the relevant time expressions from the natural sentences and find the relations among them. Location information is the absolute geological location or relative geological location of the words that are present in the natural sentences. The function of the location extraction is to extract the location information and understand the relation of the location expressions in the sentences.
+
+- Continuous linguistic knowledge acquisition and extension:
+
+The function of the continuous linguistic knowledge acquisition and extension sub-functional block is to provide the functionality for the IQAS to be able to answer to the user's questions reflecting continuously changing real-world environments. This functionality is composed of two functions: the updating function of natural language understanding (NLU) analysis results and the framework function to learn and extend language knowledge based on the continuous updates. The updating function of NLU results includes a metadata saving sub-module which saves intermediate results to produce language analysis results. Another sub-module of the updating function of NLU, the updating sub-module analyses the saved metadata again based on the new language knowledge and then updates the existing language analysis results based on the re-analysed results of the metadata.
+
+The framework function to learn and extend language knowledge based on the continuous updates includes the sub-modules such as the plug-in function for the continuous learning, the workflow function, the document collecting function, the continuous engine function, the monitoring function for the system learning process and the workbench for learning verification function.
+
+
+
+```
+graph LR; A[(Natural language understanding result)] --> B[Linguistic knowledge learning and extraction function]; subgraph B; B1[Time/location information extraction]; B2[Semantic relation extraction]; B3[Continuous linguistic knowledge extraction framework]; B4[Continuous NLU result update]; B1 --> B3; B2 --> B3; B3 --> B4; end;
+```
+
+F.746.3(15)\_F04
+
+Figure 4 – Logical block diagram of the linguistic knowledge learning and extraction function. The diagram shows a flow starting from 'Natural language understanding result' (cylinder) pointing to a dashed box labeled 'Linguistic knowledge learning and extraction function'. Inside this box, the flow goes to 'Continuous linguistic knowledge extraction framework' (rectangle), which is influenced by 'Time/location information extraction' and 'Semantic relation extraction' (rectangles). The output of the framework is 'Continuous NLU result update' (rectangle).
+
+Figure 4 – Logical block diagram of the linguistic knowledge learning and extraction function
+
+## 8.2 Question analysis
+
+The question analysis functional block analyses questions which are input in a natural language by a user; it understands the user's intention and recognizes various information on the answers that should be presented as the output of the IQAS system. The question analysis functional block consists of the following functional sub-blocks:
+
+- **Question classification:** defines question types based on the question answering strategy and classifies questions.
+- **Question decomposition:** decomposes the question based on structural and semantic information and recognizes question types of sub-questions and the relations among them.
+- **Question hypothesis generation:** generates multiple paraphrased questions with the same meaning of the user's question. The generated paraphrased questions are input to the QA engine and candidate answers are extracted. After integrated ranking of the candidate answers, the final answer is presented to the user. The ranking of the paraphrased question hypotheses are decided by evaluating meaning preservation, grammar preservation and the general expressiveness of the questions.
+- **Question focus and answer type recognition:** recognizes the words or phrases that can replace the candidate answer as a question focus and answer type. The answer types are of lexical answer type and semantic answer type.
+- **Keyword extraction:** recognizes the salient keywords which match with the title of the encyclopaedia. If any ambiguity occurs in matching them, it is resolved by comparing similarities.
+- **Generation of question intermediate format:** generates intermediate question formats which are intermediate forms between the user's natural language questions and formal knowledge base queries such as SPARQL and structured query language (SQL). Question intermediate formats are represented as a logical equation with answer variables and answer restrictions extracted from the natural language question.
+- The user's knowledge level is inferred by analysing the user's question sentence, domain-specific vocabularies in use and the individualized language usage of the user.
+
+The workflow of question analysis is shown in Figure 5.
+
+
+
+```
+
+graph TD
+ Question[Question] --> QC[Question classification]
+ QC --> QD[Question decomposition]
+ subgraph QD [Question decomposition]
+ QD1[Question decomposition]
+ QD2[Classification of sub-question type]
+ QD3[Recognition of sub-question relation]
+ end
+ QD --> QPG[Question paraphrase generation]
+ QPG --> QAE[Question analysis engine]
+ subgraph QAE [Question analysis engine]
+ QFD[Question focus detection]
+ AT[Answer type recognition]
+ KE[Keyword extraction and linking]
+ end
+ QAE --> QIFG[Question intermediate format generation]
+ QIFG --> QAR[Question analysis result]
+
+```
+
+F.746.3(15)\_F05
+
+Flowchart of the question analysis workflow. The process starts with 'Question' at the top, leading to 'Question classification'. This leads to 'Question decomposition', which contains sub-steps: 'Question decomposition', 'Classification of sub-question type', and 'Recognition of sub-question relation'. This leads to 'Question paraphrase generation'. From 'Question paraphrase generation', an arrow points to a 'Question analysis engine' box. The 'Question analysis engine' contains sub-steps: 'Question focus detection', 'Answer type recognition', and 'Keyword extraction and linking'. From the 'Question analysis engine', an arrow points to 'Question intermediate format generation', which then points to 'Question analysis result'.
+
+**Figure 5 – Workflow of question analysis**
+
+In Figure 6, an example of an intermediate question format is presented with a natural language question in Korean "X-seon ul balgyeon han yi saram-un bangsanung sidae-lul yeoreotda. Nobel Mulihak Sang-ul batun yi Gwahakja-nun nuguinka? (The X-rays that this person discovered opened up the era of radiology. Who is this scientist who received the Nobel prize in physics?)"
+
+In Table 1, the interfaces among sub-blocks of the question analysis functional block are defined.
+
+| | | Word | Part of speech | Named entity | Syntactic relation | Semantic role | |
+|------------------------------|-----------|-----------|---------------------------|--------------------------------------|-----------------------------|--------------------|----------------------------------|
+| | Variable | X | | | | | |
+| Question intermediate format | Condition | Predicate | Type | | | | Type predicate semantic frame |
+| | | Argument0 | X | – | – | – | |
+| | | Argument1 | Saram (man) | Saram/NNG | | – | |
+| | | Predicate | Balgyeon ha (discover do) | Balgyeon/NNG + ha/XSV | | | Lexical predicate semantic frame |
+| | | Argument0 | X | – | – | NP_SBJ ARG0 | |
+| | | Argument1 | X seon (ray) | X/SL + seon/NNG | – | VP_MOD ARG1 | |
+| | | | Word | Part of speech | Named entity | Syntactic relation | Semantic role |
+| | Variable | Y | | | | | |
+| | Condition | Predicate | Type | | | | Type predicate semantic frame |
+| | | Argument0 | Y | – | – | – | |
+| | | Argument1 | Gwahakja (scientist) | Gwahak/NNG + ja/XSNG | Gwahakja/CV_OCCUPATION | – | |
+| | | Predicate | Bat (receive) | Bat/VV | | | Lexical predicate semantic frame |
+| | | Argument0 | Y | – | – | VP_MOD ARG0 | |
+| | | Argument1 | Nobel Mulihak Sang | Nobel/NNP+muli/NNG +hak/XSN+sang/XSN | Nobel Mulihak Sang/CV_PRIZE | NP_OBJ ARG1 | |
+
+F.746.3(15)\_F06
+
+**Figure 6 – Example of an intermediate question format**
+
+**Table 1 – Interface of question analysis functional sub-blocks**
+
+| Functions | Input | Output |
+|--------------------------------------------|----------------------------------------------------------------------------|------------------------------------------------------------------------------|
+| Question classification | Questions | Question type |
+| Question decomposition | Question with question type attached | Sub-question and relations among sub-questions |
+| Question hypothesis generation | Question, decomposed sub-questions | Question hypothesis with reliability |
+| Question focus and answer type recognition | Question, answer type dictionary | Question focus and answer type |
+| Keyword extraction | Question, title lists of encyclopaedia | Title, title identifier (ID) of encyclopaedia |
+| Generation of intermediate question format | NLP analysed question, information extracted, answer types, question focus | Question semantic frame list representing answer constraints in logical form |
+
+## 8.3 Candidate answer generation
+
+The candidate answer generation module performs the index and search functions on the document collections and generates candidate answers using search results and various databases. The module then determines the ranking of the candidate answers by using methods such as type coercion, time/location inferences and calculation of similarities among sentences. The candidate answer generation functions involve sub-functions such as real-time information search, real-time candidate answer generation and multi-source/text-based/KB-based candidate answer generation.
+
+- **Real-time information search:** The target of the real-time information search includes the general document collections, as well as the open user-created encyclopaedia such as Wikipedia. When searching for the information in the open user-created encyclopaedia, the IQAS also uses the unstructured and semi-structured information. In the open user-created encyclopaedia, the main text and definitions are unstructured information and section title document, category document and info-box document are semi-structured information. The information search module consists of an indexing stage and a searching stage. The indexing function takes the unstructured text as input and generates multiple indexed databases. The searching function searches for similar documents from the indexed databases based on the question analysis results. It provides as a result document contents, rankings and weights.
+- **KB-based answer generation:** This sub-function generates KB questions which are specified by each KB based on the question intermediate format produced during the question analysis stage. It then searches each KB and generates candidate answers. The KB-specific questions are generated by the following steps: The arguments of the question intermediate format are mapped onto the classes or instances defined in the specific KB; The predicate of the question intermediate format is mapped to the property defined in the specific KB; The KB-specific questions are searched for and generated in the specific KB, and finally the candidate answers are generated.
+
+## 8.4 Answer inference and generation
+
+The function of the answer inference and generation module is to decide upon and generate the best answer from among the candidate answers by measuring reliabilities based on multiple knowledge sources of different types. The inference and generation module performs feature normalization and ranking of the candidate answers by learning the reliability thresholds according to the question types. The best answer is synthesized and finally presented to the user as the output of the question answering service.
+
+## Bibliography
+
+- [b-ITU-T H.760] Recommendation ITU-T H.760 (2009), *Overview of multimedia application frameworks for IPTV services.*
+- [b-ITU-T H.780] Recommendation ITU-T H.780 (2012), *Digital signage: Service requirements and IPTV-based architecture.*
+- [b-ITU-T Y.101] Recommendation ITU-T Y.101 (2000), *Global Information Infrastructure terminology: Terms and definitions.*
+- [b-FrameNet] FrameNet.
+<>
+
+
+
+
+
+## SERIES OF ITU-T RECOMMENDATIONS
+
+| | |
+|-----------------|-----------------------------------------------------------------------------------------------------------------------------------------------------------|
+| Series A | Organization of the work of ITU-T |
+| Series D | General tariff principles |
+| Series E | Overall network operation, telephone service, service operation and human factors |
+| Series F | Non-telephone telecommunication services |
+| Series G | Transmission systems and media, digital systems and networks |
+| Series H | Audiovisual and multimedia systems |
+| Series I | Integrated services digital network |
+| Series J | Cable networks and transmission of television, sound programme and other multimedia signals |
+| Series K | Protection against interference |
+| Series L | Environment and ICTs, climate change, e-waste, energy efficiency; construction, installation and protection of cables and other elements of outside plant |
+| Series M | Telecommunication management, including TMN and network maintenance |
+| Series N | Maintenance: international sound programme and television transmission circuits |
+| Series O | Specifications of measuring equipment |
+| Series P | Terminals and subjective and objective assessment methods |
+| Series Q | Switching and signalling |
+| Series R | Telegraph transmission |
+| Series S | Telegraph services terminal equipment |
+| Series T | Terminals for telematic services |
+| Series U | Telegraph switching |
+| Series V | Data communication over the telephone network |
+| Series X | Data networks, open system communications and security |
+| Series Y | Global information infrastructure, Internet protocol aspects, next-generation networks, Internet of Things and smart cities |
+| Series Z | Languages and general software aspects for telecommunication systems |
\ No newline at end of file
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+
+
+**ITU-T**
+
+TELECOMMUNICATION
+STANDARDIZATION SECTOR
+OF ITU
+
+**F.746.4**
+
+(03/2017)
+
+SERIES F: NON-TELEPHONE TELECOMMUNICATION
+SERVICES
+
+Multimedia services
+
+---
+
+**Requirements for deployment of information-
+centric networks**
+
+Recommendation ITU-T F.746.4
+
+# ITU-T F-SERIES RECOMMENDATIONS **NON-TELEPHONE TELECOMMUNICATION SERVICES**
+
+| | |
+|-----------------------------------------------------------------|--------------------|
+| TELEGRAPH SERVICE | |
+| Operating methods for the international public telegram service | F.1–F.19 |
+| The gentex network | F.20–F.29 |
+| Message switching | F.30–F.39 |
+| The international telemessage service | F.40–F.58 |
+| The international telex service | F.59–F.89 |
+| Statistics and publications on international telegraph services | F.90–F.99 |
+| Scheduled and leased communication services | F.100–F.104 |
+| Phototelegraph service | F.105–F.109 |
+| MOBILE SERVICE | |
+| Mobile services and multdestination satellite services | F.110–F.159 |
+| TELEMATIC SERVICES | |
+| Public facsimile service | F.160–F.199 |
+| Teletex service | F.200–F.299 |
+| Videotex service | F.300–F.349 |
+| General provisions for telematic services | F.350–F.399 |
+| MESSAGE HANDLING SERVICES | F.400–F.499 |
+| DIRECTORY SERVICES | F.500–F.549 |
+| DOCUMENT COMMUNICATION | |
+| Document communication | F.550–F.579 |
+| Programming communication interfaces | F.580–F.599 |
+| DATA TRANSMISSION SERVICES | F.600–F.699 |
+| MULTIMEDIA SERVICES | F.700–F.799 |
+| ISDN SERVICES | F.800–F.849 |
+| UNIVERSAL PERSONAL TELECOMMUNICATION | F.850–F.899 |
+| ACCESSIBILITY AND HUMAN FACTORS | F.900–F.999 |
+
+*For further details, please refer to the list of ITU-T Recommendations.*
+
+# Recommendation ITU-T F.746.4
+
+## Requirements for deployment of information-centric networks
+
+## Summary
+
+Recommendation ITU-T F.746.4 describes the scenarios and requirements for deployment of information-centric networks (ICNs). The deployment supports flexible methods for deploying various ICN instances on a single network service provider (NSP) network, deploying an ICN instance over multiple NSP networks, and interoperating between different ICN instances. The framework requires decoupling of the data plane and the control plane; in addition, one or more switches and controllers supporting such deployment are required. The software and hardware resources in the switches and controllers are required to be virtualized and to be used to create ICN instances. There exist appropriate inter-ICN service provider interfaces to facilitate interoperations of two ICN instances.
+
+## History
+
+| Edition | Recommendation | Approval | Study Group | Unique ID* |
+|---------|----------------|------------|-------------|---------------------------------------------------------------------------|
+| 1.0 | ITU-T F.746.4 | 2017-03-01 | 16 | 11.1002/1000/13179 |
+
+## Keywords
+
+Deployment, information-centric networks, interoperation, software-defined networking.
+
+---
+
+\* To access the Recommendation, type the URL in the address field of your web browser, followed by the Recommendation's unique ID. For example, .
+
+## FOREWORD
+
+The International Telecommunication Union (ITU) is the United Nations specialized agency in the field of telecommunications, information and communication technologies (ICTs). The ITU Telecommunication Standardization Sector (ITU-T) is a permanent organ of ITU. ITU-T is responsible for studying technical, operating and tariff questions and issuing Recommendations on them with a view to standardizing telecommunications on a worldwide basis.
+
+The World Telecommunication Standardization Assembly (WTSA), which meets every four years, establishes the topics for study by the ITU-T study groups which, in turn, produce Recommendations on these topics.
+
+The approval of ITU-T Recommendations is covered by the procedure laid down in WTSA Resolution 1.
+
+In some areas of information technology which fall within ITU-T's purview, the necessary standards are prepared on a collaborative basis with ISO and IEC.
+
+## NOTE
+
+In this Recommendation, the expression "Administration" is used for conciseness to indicate both a telecommunication administration and a recognized operating agency.
+
+Compliance with this Recommendation is voluntary. However, the Recommendation may contain certain mandatory provisions (to ensure, e.g., interoperability or applicability) and compliance with the Recommendation is achieved when all of these mandatory provisions are met. The words "shall" or some other obligatory language such as "must" and the negative equivalents are used to express requirements. The use of such words does not suggest that compliance with the Recommendation is required of any party.
+
+## INTELLECTUAL PROPERTY RIGHTS
+
+ITU draws attention to the possibility that the practice or implementation of this Recommendation may involve the use of a claimed Intellectual Property Right. ITU takes no position concerning the evidence, validity or applicability of claimed Intellectual Property Rights, whether asserted by ITU members or others outside of the Recommendation development process.
+
+As of the date of approval of this Recommendation, ITU had not received notice of intellectual property, protected by patents, which may be required to implement this Recommendation. However, implementers are cautioned that this may not represent the latest information and are therefore strongly urged to consult the TSB patent database at .
+
+© ITU 2017
+
+All rights reserved. No part of this publication may be reproduced, by any means whatsoever, without the prior written permission of ITU.
+
+## Table of Contents
+
+| | Page |
+|------------------------------------------------------------------------|------|
+| 1 Scope..... | 1 |
+| 2 References..... | 1 |
+| 3 Definitions ..... | 1 |
+| 3.1 Terms defined elsewhere ..... | 1 |
+| 3.2 Terms defined within this document ..... | 1 |
+| 4 Abbreviations and acronyms ..... | 1 |
+| 5 Convention..... | 2 |
+| 6 Background..... | 2 |
+| 7 Requirements for the deployment of ICNs..... | 3 |
+| 7.1 General requirements..... | 3 |
+| 7.2 Requirements for the switch supporting the deployment..... | 3 |
+| 7.3 Requirements for the controller supporting the deployment..... | 3 |
+| 8 A framework for deployment of an ICN ..... | 4 |
+| 8.1 Switch supporting the deployment ..... | 4 |
+| 8.2 Controller supporting the deployment..... | 5 |
+| 9 Security considerations ..... | 5 |
+| Annex A – Scenarios of ICN deployment ..... | 6 |
+| A.1 Scenario of a single ICN instance over multiple NSP networks ..... | 6 |
+| A.2 Scenario of multiple ICN instances on a single NSP network ..... | 7 |
+| A.3 Scenario of interoperation between ICN instances ..... | 8 |
+| Bibliography..... | 9 |
+
+
+
+# Recommendation ITU-T F.746.4
+
+## Requirements for deployment of information-centric networks
+
+# 1 Scope
+
+This Recommendation describes the scenarios and requirements for deployment of information-centric networks (ICNs). The deployment supports flexible methods for deploying various ICN instances on a single network service provider (NSP) network, deploying an ICN instance over multiple NSP networks, and interoperating between different ICN instances.
+
+This Recommendation describes scenarios and common requirements for the deployment of ICNs. It also presents the framework for the deployment. This Recommendation covers the following:
+
+- scenarios of the deployment of an ICN;
+- requirements of the deployment of an ICN and its key components;
+- framework for the deployment of an ICN.
+
+# 2 References
+
+The following ITU-T Recommendations and other references contain provisions which, through reference in this text, constitute provisions of this Recommendation. At the time of publication, the editions indicated were valid. All Recommendations and other references are subject to revision; users of this Recommendation are therefore encouraged to investigate the possibility of applying the most recent edition of the Recommendations and other references listed below. A list of the currently valid ITU-T Recommendations is regularly published. The reference to a document within this Recommendation does not give it, as a stand-alone document, the status of a Recommendation.
+
+[ITU-T Y.3001] Recommendation ITU-T Y.3001 (2011), *Future networks: Objectives and design goals*.
+
+# 3 Definitions
+
+## 3.1 Terms defined elsewhere
+
+This Recommendation uses the following term defined elsewhere:
+
+**3.1.1 future network** [ITU-T Y.3001]: A network able to provide services, capabilities, and facilities difficult to provide using existing network technologies. A future network is either:
+
+- a) A new component network or an enhanced version of an existing one, or
+- b) A heterogeneous collection of new component networks or of new and existing component networks that is operated as a single network.
+
+## 3.2 Terms defined within this document
+
+None.
+
+# 4 Abbreviations and acronyms
+
+This Recommendation uses the following abbreviations and acronyms:
+
+| | |
+|-------|-----------------------------------|
+| API | Application Programming Interface |
+| CONET | Content Networking |
+| FN | Future Network |
+
+| | |
+|---------|---------------------------------------|
+| ICN | Information-Centric Network |
+| NDN | Named Data Networking |
+| NetInf | Network of information |
+| NSP | Network Service Provider |
+| PURSUIT | Publish–Subscribe Internet Technology |
+| SDN | Software-Defined Networking |
+
+# 5 Convention
+
+In this Recommendation:
+
+- The expression "**is required to**" indicates a requirement which must be strictly followed and from which no deviation is permitted if conformance to this Recommendation is to be claimed.
+- The expression "**is recommended**" indicates a requirement which is recommended but not absolutely required. Thus this requirement need not be present to claim conformance.
+
+# 6 Background
+
+In recent years, future networks (FNs) as described in [ITU-T Y.3001] have attracted considerable attention from both academia and industry. One FN objective is data awareness, which enables retrieval of data regardless of their location. To achieve this objective, the concept of information-centric networks (ICNs) has been proposed together with various ICN architectures [b-ITU-T Y.3033], [b-Dannewitz], [b-Jacobson], [b-Särelä], [b-Seskar], [b-Detti]. The next major challenge is to convince network service providers (NSPs) around the globe to adopt the concept of ICN and to deploy ICN-enabled networks.
+
+To achieve this goal, many prototypes and testbeds have been developed. In general, these proof-of-concept systems can be implemented by two approaches: overlay and non-overlay. With the first approach, some special overlay nodes are deployed to deal with ICN protocol-related operations on top of an existing physical network. For example, overlay-based systems have been developed for named data networking (NDN) [b-Jacobson] and network of information (NetInf) [b-Dannewitz].
+
+In contrast, in the non-overlay approach, ICN functions are implemented in routers directly. For instance, the prototype of Publish–Subscribe Internet Technology (PURSUIT) [b-Särelä] has been developed based on the Click modular router [b-Kohler], which allows network designers to create their own routers based on general-purpose personal computer hardware. Besides that, some ICN projects, such as MobilityFirst [b-Seskar] and content networking (CONET) [b-Detti], developed their prototypes based on software-defined networking (SDN), which provides programmability to networks.
+
+Despite the importance of these prototypes, the deployment of ICN is still an open question. One obvious reason is that there are too many ICN candidates, which have different design principles and various technical details in terms of naming, routing, and so on. Taking content access as an example, while most ICN architectures are based on the assumption that a user will initiate a request and expect to access the content object as soon as possible, the PURSUIT project is based on the publish–subscribe model, in which both publisher and subscriber register on the ICN, and the publisher can push content whenever it is generated. Clearly, these two approaches can be applied by different types of application to optimize their performance.
+
+As each ICN architecture has its own pros and cons and is best suited to some particular application requirements, various ICN architectures will be adopted. On the other hand, different ICN service
+
+providers can also implement their own ICN instances to provide specific services for users. For instance, one ICN service provider provides streaming service and another ICN service provider provides instant message service. Thus, various ICN instances will coexist on top of the same physical network.
+
+Nevertheless, existing ICN prototypes only focus on the implementation of individual ICN architectures. Neither the coexistence of multiple ICN instances in the same physical network nor the requirement for interoperation of different ICN instances is considered.
+
+This Recommendation focuses on the issue of the deployment of ICNs, including the scenarios, requirements and framework.
+
+# **7 Requirements for the deployment of ICNs**
+
+## **7.1 General requirements**
+
+GEN-01: The deployment framework is required to decouple the data plane and the control plane. One or multiple switches and controllers supporting such deployment are required.
+
+GEN-02: The deployment framework is required to virtualize the resources of network infrastructure to facilitate ICN implementation and coexistence. That is, the software and hardware resources in switches and controllers are required to be virtualized and to be provided to ICN instances.
+
+GEN-03: The deployment framework is required to define appropriate inter-ICN service provider interfaces to facilitate interoperations between two ICN instances.
+
+GEN-04: The deployment framework is required to provide basic general functions, including name-based routing, in-network cache management and content-based security.
+
+## **7.2 Requirements for the switch supporting the deployment**
+
+DS-01: A switch is required to support general ICN-related operations and to process received packets according to the defined rules configured by control programs (i.e., ICN instances). The general ICN-related operations include name-based routing, in-network caching and content-based security.
+
+DS-02: A switch is required to provide the following primitive functions: forwarding packets and caching traversed content.
+
+DS-03: A switch is required to support virtualization for the implementation and coexistence of multiple ICN instances in the data plane. That is, the forwarding table and storage of the switch require allocation to different ICN instances to guarantee the required service quality. Packets belonging to different ICN instances require delivery to the appropriate control program and forwarding to appropriate interfaces.
+
+DS-04: A switch is required to provide interfaces for ICN instances to manipulate the allocated resources, including the forwarding table and storage.
+
+DS-05: A switch is recommended to provide the general ICN-related functions as modules.
+
+DS-06: A switch is recommended to support interoperation, including re-encapsulating packets and sending requests according to the rules configured by the control programs.
+
+## **7.3 Requirements for the controller supporting the deployment**
+
+DC-01: A controller is required to provide interfaces for an ICN service provider to deploy their own ICN instances in the control plane with full control of the physical resources.
+
+DC-02: A controller is required to support virtualization for the coexistence of multiple ICN instances.
+
+DC-03: A controller is required to support the registration of an ICN service provider.
+
+DC-04: A controller is required to support the registration of switches which support the deployment.
+
+DC-05: A controller is required to provide interfaces between different ICN instances to mutually exchange control information.
+
+DC-06: A controller is recommended to provide general ICN-related functions as modules, including routing manager, content manager, storage manager, security manager and interoperation manager.
+
+# 8 A framework for deployment of an ICN
+
+This clause addresses the capabilities of the switch and controller.
+
+Figure 8-1 shows the details of the switch and controller framework supporting the deployment.
+
+
+
+The diagram illustrates the framework for deployment of an ICN. It consists of two main components: a Controller and a Switch, both supporting the deployment.
+
+**Controller:** The controller is represented by a server icon and contains multiple ICN instances (ICN instance 1 to ICN instance N). Each ICN instance contains a set of managers: Inter-operation manager, Security manager, Storage manager, Content manager, and Routing manager. All ICN instances are connected to a central ICN instances manager. The ICN instances manager is connected to the Switch via a Secure channel.
+
+**Switch:** The switch is represented by a switch icon and is divided into Software and Hardware layers.
+
+**Software Layer:** The software layer contains an ICN instance management API. Below this API, there are multiple ICN instances (ICN instance 1 to ICN instance N). Each ICN instance contains a set of APIs: Inter-operation API, Forwarding table API, and Storage management API. The ICN instance management API is connected to the ICN instances manager in the Controller.
+
+**Hardware Layer:** The hardware layer contains the following elements: Inter-operation logic, Forwarding management logic, Storage management logic, Forwarding table, Storage, and a Switching element. The Switching element is connected to the Forwarding table and Storage. The Forwarding management logic and Storage management logic are connected to the Forwarding table and Storage respectively. The Inter-operation logic is connected to the Forwarding management logic and Storage management logic.
+
+Figure 8-1: A switch and controller framework supporting the deployment. The diagram shows a Controller and a Switch, both supporting the deployment. The Controller contains multiple ICN instances (1 to N) with internal managers (Inter-operation, Security, Storage, Content, Routing) and an ICN instances manager. The Switch is divided into Software and Hardware layers. The Software layer contains an ICN instance management API and multiple ICN instances (1 to N) with internal APIs (Inter-operation, Forwarding table, Storage management). The Hardware layer contains Inter-operation logic, Forwarding management logic, Storage management logic, Forwarding table, Storage, and a Switching element. A secure channel connects the Controller's ICN instances manager to the Switch's ICN instance management API.
+
+Figure 8-1 – A switch and controller framework supporting the deployment
+
+## 8.1 Switch supporting the deployment
+
+The switch, consisting of the hardware and software systems, is responsible for forwarding packets belonging to different ICN instances. To support various ICN-related operations, including local caching decision and name recognition, there are six hardware elements in the hardware system: switching element, forwarding table, storage, forwarding management logic, storage management
+
+logic and interoperation logic. These hardware resources are shared by different ICN instances. Such hardware resources are virtualized into different slices, each of which is dedicated to a particular ICN instance.
+
+The switch provides interfaces, including forwarding table application programming interfaces (APIs), storage management APIs and interoperation APIs, to ICN instances to manage the resources allocated to them. The forwarding table API is used to instruct the forwarding management logic to manipulate one or more forwarding tables for a particular ICN instance. The storage management API is responsible for managing local caching policy in storage management logic or caching content in the content storage under the control of the controller. The interoperation API is designed to guide the interoperation logic to encapsulate packets or perform protocol translation received from an incompatible user.
+
+## **8.2 Controller supporting the deployment**
+
+The controller is responsible for managing virtualized physical network resources for each ICN instance. The controller provides five functions for ICN service providers, as shown in Figure 8-1. The content manager is responsible for maintaining information about content sources and destinations. The routing manager is used to maintain the topology of this ICN instance and perform ICN-related routing algorithms. The storage manager is used to set the policies for managing physical content storage. The security manager is responsible for providing secure service. The interoperation manager is used to guide the interoperation with other ICN instances. Each ICN service provider can deploy its own ICN instance according to the specification of a particular ICN architecture by selecting appropriate modules to instantiate.
+
+# **9 Security considerations**
+
+This Recommendation has some security considerations similar to those pertinent to data aware networking and aligns with the security requirements specified in [b-ITU-T Y.3033]. The channels between controller and switch and that among controllers are required to be secured and also have good privacy protection.
+
+# Annex A
+
+## Scenarios of ICN deployment
+
+(This annex forms an integral part of this Recommendation.)
+
+A general scenario for the deployment of an ICN is shown in Figure A.1.
+
+Each NSP network supporting the deployment consists of two types of networking elements, i.e., switch and controller. For example, in Figure A.1 there are two NSP networks (i.e., NSP1 and NSP2).
+
+Multiple ICN instances can coexist and each of them is owned by a particular operator, which is defined as an ICN service provider. Different ICN instances may adopt different ICN architectures.
+
+Each ICN instance has its own group of users. A user of one ICN service provider may move to a geographical area that their ICN service provider does not cover. For example, a user of ICN service provider 1 may move to a place covered only by ICN service provider 4.
+
+
+
+The diagram illustrates the three-tier architecture of ICN deployment. The top tier, labeled 'ICN users', contains four groups of devices (laptop, server, smartphone) in purple, yellow, orange, and blue ovals. The middle tier, labeled 'ICN instances', contains four corresponding service provider ovals. The bottom tier, labeled 'NSP networks', shows two network clusters, NSP1 and NSP2, each with multiple switches (cylinder icons with red 'X') and two central controllers (server rack icons). Solid lines represent data channels between users and instances, and between switches. Dashed lines represent control channels between controllers. Dash-dot lines represent virtual channels between different ICN service providers across the NSP networks.
+
+Legend:
+
+- Switch supporting the deployment (cylinder icon with red 'X')
+- Controller supporting the deployment (server rack icon)
+- Data channel (solid line)
+- Control channel (dashed line)
+- Virtual channel between ICN service providers (dash-dot line)
+
+Figure A.1: An overview of ICN deployment. The diagram shows three layers: ICN users at the top, ICN instances in the middle, and NSP networks at the bottom. ICN users are connected to ICN instances via solid vertical arrows. ICN instances are connected to NSP networks via dashed vertical arrows. NSP networks are connected to each other via solid horizontal arrows. A legend at the bottom defines the symbols: a switch icon for 'Switch supporting the deployment', a controller icon for 'Controller supporting the deployment', a solid line for 'Data channel', a dashed line for 'Control channel', and a dash-dot line for 'Virtual channel between ICN service providers'.
+
+F.746.4(17)\_FA.1
+
+Figure A.1 – An overview of ICN deployment
+
+### A.1 Scenario of a single ICN instance over multiple NSP networks
+
+As ICN instances are implemented on top of NSP networks to provide content delivery service, one common implementation scenario for the deployment is when one ICN instance is implemented over multiple NSP networks. To guarantee service quality, one ICN service provider can rent resources from multiple NSP networks to deploy its own ICN and to optimize content delivery efficiency.
+
+For instance, ICN service provider 3 in Figure A.2 is built on the networks of both NSP1 and NSP2. A user associated with ICN service provider 3 needs not be aware of the underlying NSP networks. When the user moves from one location on the NSP1 network to another in NSP2, it gets uninterrupted service from ICN Service Provider 3.
+
+To facilitate an ICN instance across multiple NSP networks, both the data channels and control channels to allow the interconnection are provided.
+
+The data channel is used for data transmission. The control channel is used to exchange control information, e.g., routing and interconnection information. With such information, ICN service provider 3 sets up communications across multiple NSP networks and provides unified service to its users.
+
+
+
+The diagram illustrates a single ICN instance spanning two network service provider (NSP) domains, NSP1 and NSP2, and an ICN service provider (ICNSP3). At the top, two laptops are connected to a central oval labeled 'ICNSP3'. Below this, two separate network clouds represent NSP1 and NSP2. Each cloud contains a 'Controller' (server icon), a 'Switch' (cylinder icon), and two routers (cylinder icons with red 'X' marks). A dashed line labeled 'Control channel' connects the controllers of NSP1 and NSP2. A solid line labeled 'Data channel' connects the routers of NSP1 and NSP2. Dashed lines also connect the laptops to the controllers of NSP1 and NSP2. The label 'F.746.4(17)\_FA.2' is in the bottom right corner.
+
+Diagram of a single ICN instance across multiple NSP networks.
+
+**Figure A.2 – A single ICN instance deployed over multiple NSP networks**
+
+### A.2 Scenario of multiple ICN instances on a single NSP network
+
+Since different ICN architectures have their own pros and cons, multiple ICN instances employing different ICN architectures can coexist on the same NSP network.
+
+One NSP network supports multiple ICN service providers. Each of them creates its own ICN instance to provide optimized services to its own users. For example, as shown in Figure A.3, ICN service provider 1 may choose NDN to provide services with the aim of optimizing video streaming, while ICN service provider 2 may adopt PURSUIT to provide services to efficiently facilitate online social networking.
+
+To allow the creation of multiple ICN instances on a single NSP network, a set of interfaces is provided such that ICN service providers can perform ICN architecture-related operations (name-based routing, in-network caching, etc.). The traffic belonging to different ICN instances is processed independently.
+
+
+
+The diagram shows two ICN service providers, 'ICN service provider 1' and 'ICN service provider 2', connected to a single NSP network cloud labeled 'NSP1'. Inside the NSP1 cloud, there is a 'Controller' (server icon), a 'Switch' (cylinder icon), and two routers (cylinder icons with red 'X' marks). Dashed lines connect 'ICN service provider 1' to the controller and routers. Another set of dashed lines connects 'ICN service provider 2' to the same controller and routers. The label 'F.746.4(17)\_FA.3' is in the bottom right corner.
+
+Diagram of multiple ICN instances on a single NSP network.
+
+**Figure A.3 – Multiple ICN instances deployed on a single NSP network**
+
+### A.3 Scenario of interoperation between ICN instances
+
+A user of one ICN service provider may need to access services from another ICN service provider, where the two ICN service providers adopt different ICN architectures as shown in Figure A.4.
+
+One example is that a user in ICN service provider 1 needs a content object which is owned by a server in ICN service provider 2 as shown in Figure A.4 a). Another example is that a user of ICN service provider 1 moves to a geographical area that is not covered by the underlying NSP1 of ICN service provider 1 as shown in Figure A.4 b).
+
+There are two ways to support interoperation. The first is tunnelling, with which a user of one ICN service provider can connect to its ICN instance via tunnels established in another ICN instance. The second is to perform protocol translation in the border switch.
+
+
+
+The diagram illustrates two scenarios for ICN interoperation.
+Part (a), titled 'a) Within the same NSP', shows a 'User' and a 'Server' connected to 'ICN service provider 1' and 'ICN service provider 2' respectively. Both providers are connected to a single network domain labeled 'NSP1'. Inside NSP1, there is a 'Controller' and two 'Switch' nodes. A dashed line connects the User to the Server, passing through both service providers and into the NSP1 infrastructure.
+Part (b), titled 'b) Across different NSPs', shows a 'User' connected to 'ICN service provider 1' and another 'User' connected to 'ICN service provider 4'. 'ICN service provider 1' is connected to 'NSP1', which contains a 'Controller' and 'Switch' nodes. 'ICN service provider 4' is connected to 'NSP2', which also contains a 'Controller' and 'Switch' nodes. A 'Control channel' (dashed line) and a 'Data channel' (solid line) connect the controllers of NSP1 and NSP2. A curved arrow indicates a connection between the two Users, spanning across the different service providers and network domains.
+
+Figure A.4 – Interoperation of two ICN instances. The diagram is divided into two parts: (a) Within the same NSP and (b) Across different NSPs. Part (a) shows a User and a Server connected to ICN service provider 1 and ICN service provider 2 respectively, which are both connected to a single NSP1 containing a Controller and Switches. Part (b) shows a User connected to ICN service provider 1 and another User connected to ICN service provider 4. ICN service provider 1 is connected to NSP1, and ICN service provider 4 is connected to NSP2. NSP1 and NSP2 are connected via a Control channel and a Data channel.
+
+**Figure A.4 – Interoperation of two ICN instances**
+
+F.746.4(17)\_FA.4
+
+# Bibliography
+
+- [b-ITU-T Y.3033] Recommendation ITU-T Y.3033 (2014), *Framework of data aware networking for future networks*.
+- [b-Dannewitz] Dannewitz, C. (2009). [NetInf: An information-centric design for the future Internet](#), In: *Proceedings of the 3rd GI/ITG KuVS Workshop on The Future Internet*.
+- [b-Detti] Detti A, Blefari-Melazzi N, Salsano S, Pomposini M (2011). [CONET: A content centric inter-networking architecture](#). In: *ICN 11 Proceedings of the ACM SIGCOMM Workshop on Information-centric Networking*, Toronto, ON, 2011-08-19, pp. 50–55. New York, NY: ACM.
+- [b-Jacobson] Jacobson V, Smetters DK, Thornton JD, Plass MF, Briggs NH, Braynard RL (2009). Networking named content. In: *CoNEXT '09 Proceedings of the 5th International Conference on Emerging Networking Experiments and Technologies*, Rome, 2009-12-01/04, pp. 1–12. New York, NY: ACM.
+- [b-Kohler] Kohler E, Morris R, Chen B, Jannotti J, Kaashoek MF (2000). [The Click modular router](#). *ACM Transactions on Computer Systems*, **18**(3), pp. 263–297.
+- [b-Särelä] Särelä M, Rinta-aho T, Tarkoma S (2008). RTFM: [Publish/subscribe internetworking architecture](#), In: Cunningham P, Cunningham M, eds. *ICT-Mobile Summit 2008 Conference Proceedings*, 8 pp. Dublin: IIMC International Information Management Corporation Ltd.
+- [b-Seskar] Seskar I, Nagaraja K, Nelson S, Raychaudhuri D (2011). MobilityFirst future internet architecture project. In: *AINTEC '11 Proceedings of the 7th Asian Internet Engineering Conference*, Bangkok, Thailand, 2011-09-09/11, pp. 1–3. New York, NY: ACM.
+
+
+
+
+
+## SERIES OF ITU-T RECOMMENDATIONS
+
+| | |
+|-----------------|-----------------------------------------------------------------------------------------------------------------------------------------------------------|
+| Series A | Organization of the work of ITU-T |
+| Series D | Tariff and accounting principles and international telecommunication/ICT economic and policy issues |
+| Series E | Overall network operation, telephone service, service operation and human factors |
+| Series F | Non-telephone telecommunication services |
+| Series G | Transmission systems and media, digital systems and networks |
+| Series H | Audiovisual and multimedia systems |
+| Series I | Integrated services digital network |
+| Series J | Cable networks and transmission of television, sound programme and other multimedia signals |
+| Series K | Protection against interference |
+| Series L | Environment and ICTs, climate change, e-waste, energy efficiency; construction, installation and protection of cables and other elements of outside plant |
+| Series M | Telecommunication management, including TMN and network maintenance |
+| Series N | Maintenance: international sound programme and television transmission circuits |
+| Series O | Specifications of measuring equipment |
+| Series P | Telephone transmission quality, telephone installations, local line networks |
+| Series Q | Switching and signalling, and associated measurements and tests |
+| Series R | Telegraph transmission |
+| Series S | Telegraph services terminal equipment |
+| Series T | Terminals for telematic services |
+| Series U | Telegraph switching |
+| Series V | Data communication over the telephone network |
+| Series X | Data networks, open system communications and security |
+| Series Y | Global information infrastructure, Internet protocol aspects, next-generation networks, Internet of Things and smart cities |
+| Series Z | Languages and general software aspects for telecommunication systems |
\ No newline at end of file
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+
+
+I n t e r n a t i o n a l T e l e c o m m u n i c a t i o n U n i o n
+
+# **ITU-T**
+
+TELECOMMUNICATION
+STANDARDIZATION SECTOR
+OF ITU
+
+# **F.746.5**
+
+(12/2017)
+
+SERIES F: NON-TELEPHONE TELECOMMUNICATION
+SERVICES
+
+Multimedia services
+
+---
+
+**Framework for a language learning system
+based on speech and natural language
+processing (NLP) technology**
+
+Recommendation ITU-T F.746.5
+
+**ITU-T**
+
+
+
+The logo of the International Telecommunication Union (ITU) is located in the bottom right corner. It features a stylized globe with a red lightning bolt striking across it. To the right of the globe, the text "ITU" is written in a bold, blue font, and below it, "International Telecommunication Union" is written in a smaller, blue font.
+
+ITU logo: A globe with a red lightning bolt and the text 'ITU International Telecommunication Union'.
+
+# ITU-T F-SERIES RECOMMENDATIONS **NON-TELEPHONE TELECOMMUNICATION SERVICES**
+
+| | |
+|-----------------------------------------------------------------|--------------------|
+| TELEGRAPH SERVICE | |
+| Operating methods for the international public telegram service | F.1–F.19 |
+| The gentex network | F.20–F.29 |
+| Message switching | F.30–F.39 |
+| The international telemessage service | F.40–F.58 |
+| The international telex service | F.59–F.89 |
+| Statistics and publications on international telegraph services | F.90–F.99 |
+| Scheduled and leased communication services | F.100–F.104 |
+| Phototelegraph service | F.105–F.109 |
+| MOBILE SERVICE | |
+| Mobile services and multdestination satellite services | F.110–F.159 |
+| TELEMATIC SERVICES | |
+| Public facsimile service | F.160–F.199 |
+| Teletex service | F.200–F.299 |
+| Videotex service | F.300–F.349 |
+| General provisions for telematic services | F.350–F.399 |
+| MESSAGE HANDLING SERVICES | F.400–F.499 |
+| DIRECTORY SERVICES | F.500–F.549 |
+| DOCUMENT COMMUNICATION | |
+| Document communication | F.550–F.579 |
+| Programming communication interfaces | F.580–F.599 |
+| DATA TRANSMISSION SERVICES | F.600–F.699 |
+| MULTIMEDIA SERVICES | F.700–F.799 |
+| ISDN SERVICES | F.800–F.849 |
+| UNIVERSAL PERSONAL TELECOMMUNICATION | F.850–F.899 |
+| ACCESSIBILITY AND HUMAN FACTORS | F.900–F.999 |
+
+*For further details, please refer to the list of ITU-T Recommendations.*
+
+# Recommendation ITU-T F.746.5
+
+# Framework for a language learning system based on speech and natural language processing (NLP) technology
+
+## Summary
+
+Recommendation ITU-T F.746.5 describes functional requirements and detailed functions for the framework of a language learning system based on speech and natural language processing technology. It provides a framework for a language learning system that will serve as a reference framework for language learning systems to be developed and used as low cost tools in many educational situations. This Recommendation defines the features, general requirements and functionality to support the language learning system based on speech and natural language processing (NLP) technology. The scope covers a high-level description of architecture, terminals, servers, interface and clients. .
+
+## History
+
+| Edition | Recommendation | Approval | Study Group | Unique ID* |
+|---------|----------------|------------|-------------|---------------------------------------------------------------------------|
+| 1.0 | ITU-T F.746.5 | 2017-12-14 | 16 | 11.1002/1000/13427 |
+
+## Keywords
+
+Language learning, natural language processing, speech interface, speech recognition.
+
+---
+
+\* To access the Recommendation, type the URL in the address field of your web browser, followed by the Recommendation's unique ID. For example, .
+
+## FOREWORD
+
+The International Telecommunication Union (ITU) is the United Nations specialized agency in the field of telecommunications, information and communication technologies (ICTs). The ITU Telecommunication Standardization Sector (ITU-T) is a permanent organ of ITU. ITU-T is responsible for studying technical, operating and tariff questions and issuing Recommendations on them with a view to standardizing telecommunications on a worldwide basis.
+
+The World Telecommunication Standardization Assembly (WTSA), which meets every four years, establishes the topics for study by the ITU-T study groups which, in turn, produce Recommendations on these topics.
+
+The approval of ITU-T Recommendations is covered by the procedure laid down in WTSA Resolution 1.
+
+In some areas of information technology which fall within ITU-T's purview, the necessary standards are prepared on a collaborative basis with ISO and IEC.
+
+## NOTE
+
+In this Recommendation, the expression "Administration" is used for conciseness to indicate both a telecommunication administration and a recognized operating agency.
+
+Compliance with this Recommendation is voluntary. However, the Recommendation may contain certain mandatory provisions (to ensure, e.g., interoperability or applicability) and compliance with the Recommendation is achieved when all of these mandatory provisions are met. The words "shall" or some other obligatory language such as "must" and the negative equivalents are used to express requirements. The use of such words does not suggest that compliance with the Recommendation is required of any party.
+
+## INTELLECTUAL PROPERTY RIGHTS
+
+ITU draws attention to the possibility that the practice or implementation of this Recommendation may involve the use of a claimed Intellectual Property Right. ITU takes no position concerning the evidence, validity or applicability of claimed Intellectual Property Rights, whether asserted by ITU members or others outside of the Recommendation development process.
+
+As of the date of approval of this Recommendation, ITU had received notice of intellectual property, protected by patents, which may be required to implement this Recommendation. However, implementers are cautioned that this may not represent the latest information and are therefore strongly urged to consult the TSB patent database at .
+
+© ITU 2018
+
+All rights reserved. No part of this publication may be reproduced, by any means whatsoever, without the prior written permission of ITU.
+
+## Table of Contents
+
+| | Page |
+|---------------------------------------------------------------------------|------|
+| 1 Scope..... | 1 |
+| 2 References..... | 1 |
+| 3 Definitions ..... | 1 |
+| 3.1 Terms defined elsewhere ..... | 1 |
+| 3.2 Terms defined in this Recommendation..... | 2 |
+| 4 Abbreviations and acronyms ..... | 2 |
+| 5 Conventions ..... | 2 |
+| 6 Introduction..... | 3 |
+| 6.1 Basic concept of speech interface and NLP technology ..... | 3 |
+| 6.2 Advanced technology for dialogue-based speech interface ..... | 4 |
+| 7 Requirements for language learning system..... | 5 |
+| 8 Functional components and interfaces of a language learning system..... | 5 |
+| 8.1 Speech recognition module ..... | 6 |
+| 8.2 Natural language processing module..... | 6 |
+| 8.3 Speech synthesis module ..... | 7 |
+| 8.4 Pronunciation fluency evaluation module ..... | 7 |
+| 8.5 Dialogue processing module ..... | 8 |
+| 8.6 Dialogue understanding evaluation module ..... | 9 |
+| 8.7 Dialogue knowledge learning module..... | 9 |
+| 8.8 Language learning module ..... | 10 |
+
+
+
+# Recommendation ITU-T F.746.5
+
+## Framework for a language learning system based on speech and natural language processing (NLP) technology
+
+## 1 Scope
+
+This Recommendation presents an overview of the framework for a language learning system based on speech and natural language processing (NLP) technology. It describes the features, general requirements and functionality, which is a framework to support language-learning systems. The scope covers a high-level description of architecture, devices, servers and clients.
+
+## 2 References
+
+The following ITU-T Recommendations and other references contain provisions which, through reference in this text, constitute provisions of this document. At the time of publication, the editions indicated were valid. All Recommendations and other references are subject to revision; users of this document are therefore encouraged to investigate the possibility of applying the most recent edition of the Recommendations and other references listed below. A list of the currently valid ITU-T Recommendations is regularly published. The reference to a document within this Recommendation does not give it, as a stand-alone document, the status of a Recommendation.
+
+[ITU-T F.746.3] Recommendation ITU-T F.746.3 (2015), *Intelligent question answering service framework*.
+
+[ITU-T H.703] Recommendation ITU-T H.703 (2016), *Enhanced user interface framework for IPTV terminal devices*.
+
+## 3 Definitions
+
+### 3.1 Terms defined elsewhere
+
+This Recommendation uses the following terms defined elsewhere:
+
+**3.1.1 co-reference resolution** [ITU-T F.746.3]: A function that detects the preceding referents of the pronouns which replace the noun phrases of the input sentences.
+
+**3.1.2 named entity recognition** [ITU-T F.746.3]: A function that recognizes named entities such as PLO which are people, locations and organizations from the sentences. The PLO can be decomposed into more specific named entities depending on the applications.
+
+**3.1.3 natural language processing** [ITU-T F.746.3]: A method that analyses text in natural languages through several processes such as part-of- speech recognition, syntactic analysis and semantic analysis.
+
+**3.1.4 part-of-speech recognition** [ITU-T F.746.3]: A function that recognizes parts of speech (POS) in the sentences and assigns relevant POS tags considering contextual meaning of the target sentences.
+
+**3.1.5 semantic analysis** [ITU-T F.746.3]: A function that recognizes the semantic relations among the words around predicates that exist in the same sentence. The semantic analysis function then generates a semantic predicate-argument structure (PAS).
+
+**3.1.6 speech** [ITU-T H.703]: Speech is the vocalized form of human communication.
+
+**3.1.7 speech recognition** [ITU-T H.703]: A kind of user interface for translation of spoken words into text.
+
+**3.1.8 syntactic analysis** [ITU-T F.746.3]: A function that analyses sentence structures and generates dependency relation among words based on dependency grammars.
+
+### **3.2 Terms defined in this Recommendation**
+
+This Recommendation defines the following terms:
+
+**3.2.1 dialogue-based speech interface:** An interface based on speech, especially dialogues between the user and the device or system.
+
+**3.2.2 dialogue act:** The user's intention or purpose of the utterances in a dialogue. Example: request for information, command for action, agreement.
+
+## **4 Abbreviations and acronyms**
+
+This Recommendation uses the following abbreviations and acronyms:
+
+| | |
+|-----|---------------------------------------------------------|
+| DA | Dialogue Act |
+| DNN | Deep Neural Network |
+| HCI | Human Computer Interaction |
+| ICT | Information and Communication Technology |
+| IT | Information Technology |
+| LLS | Language Learning System Based on Speech/NLP Technology |
+| NE | Named Entity |
+| NLP | Natural Language Processing |
+| PC | Personal Computer |
+| POS | Part of Speech |
+| SMS | Short Message Service |
+| SVM | Support Vector Machines |
+| TTS | Text to Speech |
+
+## **5 Conventions**
+
+The following conventions are used in this Recommendation:
+
+- The keywords "is required to" indicate a requirement which must be strictly followed and from which no deviation is permitted, if conformance to this Recommendation is to be claimed.
+- The keywords "is prohibited from" indicate a requirement which must be strictly prohibited, if conformance to this Recommendation is to be claimed.
+- The keywords "is recommended" indicate a requirement which is recommended but which is not absolutely required. Thus, this requirement need not be present to claim conformance.
+- The keywords "is not recommended" indicate a requirement which is not recommended but which is not specifically prohibited. Thus, conformance with this Recommendation can still be claimed even if this requirement is present.
+- The keywords "can optionally" indicate an optional requirement which is permissible, without implying any sense of being recommended. This term is not intended to imply that the vendor's implementation must provide the option and the feature can be optionally enabled by the network operator/service provider. Rather, it means the vendor may optionally provide the feature and still claim conformance with this Recommendation.
+
+# 6 Introduction
+
+Language learning requires a lot of time and cost for individual learners who wish to learn foreign languages, especially when personalized education is needed for each learner with a different level of learning capabilities. The ratio of students to teachers should be minimized to have an effective learning situation for individualized learning. Advances in information and communication technology (ICT), especially those in speech/language areas have made the language learning experience less expensive and more effective for individualized learning.
+
+Speech interface and natural language processing (NLP) technology is an advanced technology that allows a computer to understand what a person says, and facilitates exchange of information in a smooth conversation with the person. Speech interface/NLP technology will likely be combined with other technologies in many application areas such as national defence, medical services, etc. Moreover, speech interface/NLP technology can also be applied to language learning systems for conversation training.
+
+NLP is a core technology for human computer interaction (HCI) and a basis for knowledge and information services. It combines syntactic analysis and semantic analysis to understand human languages. NLP technology is used for understanding a user's speech in dialogue practices in various language learning scenarios.
+
+More advanced dialogue-based speech interface technology is also being developed. The basic dialogue processing flow is shown in Figure 3. The technology recognizes and understands users' speech and generates appropriate responses in limited dialogue situations. The core dialogue processing technology is applied to foreign language learning systems that simulate one-on-one conversation training.
+
+This Recommendation provides requirements, architecture and functions for a language learning system based on speech/NLP technology.
+
+## 6.1 Basic concept of speech interface and NLP technology
+
+Speech interface and NLP technology are the next generation interface that allows a computer to understand what a person says and also facilitates the exchange of information in a smooth conversation with the person. Figure 1 shows a basic speech interface and Figure 2 shows some basic NLP modules. Recently, speech interface has become one of the essential elements in the information technology (IT) industry such as intelligent robots, telematics, the next generation personal computer (PC), and digital-home. Speech interface/NLP technology will likely be combined with other technologies in many application areas such as national defence, medical services, etc. Henceforth, speech interface/NLP technology will grow into a multimodal interface with a united input device such as voice, pen, mouse and gestures. A high-level interactive speech interface will soon be attainable by incorporating circumstantial information and the speaker's intention. Moreover, speech interface/NLP technology plays the role of a core technology for mobile web information services, and can also be applied to language learning systems for conversation training.
+
+NLP is a core technology for HCI and the basis for knowledge and information services. It combines syntactic analysis and semantic analysis to understand human languages. NLP technology is used for understanding a user's speech in dialogue practices in various language learning scenarios.
+
+
+
+```
+
+graph LR
+ subgraph Top
+ A1[Input speech] --> B1[Speech recognition] --> C1[Output text]
+ end
+ subgraph Bottom
+ A2[Input text] --> B2[Speech synthesis] --> C2[Output speech]
+ end
+
+```
+
+Figure 1: Basic speech interface flowchart showing two parallel processes: Input speech to Speech recognition to Output text, and Input text to Speech synthesis to Output speech.
+
+F.746.5(17)\_F01
+
+**Figure 1 – Basic speech interface**
+
+
+
+I am a bus driver
+
+→ I/pn am/be a/ia bus/n driver/n.
+
+→ I/pn am/be a/ia bus/n [transportation] driver/n [occupation].
+
+→ (I) am a (bus driver).
+
+→ Occupation: speaker: bus driver
+
+Figure 2: Basic NLP flows with processing modules. It shows a flow from Input speech to Part of speech analysis to Named entity recognition to Syntactic analysis to Semantic analysis. Below the flow, the sentence 'I am a bus driver' is processed through various linguistic representations, leading to the final semantic interpretation: 'Occupation: speaker: bus driver'.
+
+F.746.5(17)\_F02
+
+**Figure 2 – Basic NLP flows with processing modules**
+
+## 6.2 Advanced technology for dialogue-based speech interface
+
+More advanced technology for dialogue-based speech interface has also been developed. Figure 3 shows the basic dialogue processing flow. The technology recognizes and understands users' speech and generates appropriate responses in limited dialogue situations. The core technology is applicable to foreign language learning systems that simulate one-on-one conversation training. The core technology will also be used for natural speech interface of information services on mobile devices (smartphones, navigation terminals, etc.) or wearable devices such as smart glasses and smart watches. Using this technology, smartphones will accelerate various information services in mobile environments such as voice search, voice short message service (SMS), speech enabled virtual agents, etc. For example, the conversational speech processing technology can be applied to a high quality language learning system, and the resulting system can assess the pronunciation of students and leads the conversation to help upgrade speaking skills.
+
+
+
+```
+
+graph TD
+ subgraph Dialogue_processing [Dialogue processing]
+ direction TB
+ subgraph DBs [DBs]
+ LA[Language analysis DB]
+ S[Semantics DB]
+ DP[Dialogue pattern]
+ DAL[DA learning information]
+ end
+ DU[Dialogue understanding]
+ DUTM[Dialogue understanding training module]
+ DIC[Dialogue intention training corpus]
+ US[User speech]
+ DU <--> LA
+ DU <--> S
+ DU <--> DP
+ DU <--> DAL
+ DIC --> DUTM
+ DUTM --> DU
+ US --> DU
+ end
+
+```
+
+Figure 3: Dialogue processing flowchart. It shows 'User speech' entering a 'Dialogue understanding' block. This block is connected to a 'Language analysis DB', 'Semantics DB', 'Dialogue pattern', and 'DA learning information' DBs. Below these, a 'Dialogue understanding training module' is connected to a 'Dialogue intention training corpus' and feeds into the 'Dialogue understanding' block.
+
+F.746.5(17)\_F03
+
+**Figure 3 – Dialogue processing flow**
+
+## 7 Requirements for language learning system
+
+The general requirements for a language learning system (LLS) based on speech/NLP technology are:
+
+- LLS is required to provide speech recognition function for spontaneous speech.
+- LLS is recommended to provide dialogue processing function for spontaneous utterances.
+- LLS is recommended to provide evaluation function for spontaneous speech.
+- LLS is recommended to provide error correction function for target language grammars.
+- LLS is recommended to provide pronunciation modelling function for target language.
+- LLS is recommended to provide expression learning function for target language.
+- LLS is recommended to provide pronunciation fluency feature extraction function for target language.
+- LLS is recommended to provide automatic evaluation function for pronunciation fluency for target language.
+
+
+
+The diagram illustrates the functional architecture of a language learning system, organized into two main horizontal sections. The top section, enclosed in a dashed box, contains the 'Speech recognition' module on the left, which includes 'Sound model learning', 'Pre-processing', 'Feature extraction', 'Language model learning', and 'Input/output management'. To the right of this are 'Speech synthesis', 'Dialogue processing', 'Language learning', 'Dialogue knowledge learning', 'Pronunciation fluency evaluation', and 'Dialogue understanding evaluation'. Arrows show a flow from 'Speech recognition' to 'Speech synthesis' and 'Dialogue processing', and from 'Dialogue processing' to 'Dialogue knowledge learning' and 'Dialogue understanding evaluation'. 'Language learning' is a central node receiving input from 'Speech synthesis' and 'Dialogue knowledge learning', and sending output to 'Pronunciation fluency evaluation'. The bottom section, also in a dashed box, is labeled 'Natural language processing' and contains 'Natural language understanding' (with 'POS recognition', 'Named entity recognition', 'Syntactic analysis', 'Semantic analysis', and 'Co-reference resolution') and 'Learning and extraction of linguistic knowledge' (with 'Time/location information extraction', 'Semantic relation extraction', and 'Continuous linguistic knowledge acquisition/extraction'). Arrows show a flow from 'Natural language understanding' to 'Continuous linguistic knowledge acquisition/extraction'. A large vertical arrow points from the bottom section to the top section, specifically to the 'Language learning' node. A small label 'F.746.5(17)\_F04' is in the bottom right corner.
+
+Functional architecture of language learning system diagram
+
+**Figure 4 – Functional architecture of language learning system**
+
+## 8 Functional components and interfaces of a language learning system
+
+Figure 4 shows the functional components of a language learning system. The essential modules of the functional components are as follows:
+
+- Speech recognition module: supports speech recognition function for the user's input.
+- Natural language processing module: supports natural language processing on the language learning system.
+- Speech synthesis module: supports speech synthesis on the terminal for the system output.
+- Pronunciation fluency evaluation module: supports pronunciation fluency evaluation function for the language learning system.
+
+- Dialogue processing module: supports dialogue management and generation functions for the language learning system.
+- Dialogue understanding evaluation module: supports evaluation of the user's understanding of the dialogue.
+- Dialogue knowledge learning module: supports incremental knowledge learning on the dialogue.
+- Language learning core module: supports core language learning functions such as grammar learning and dialogue expression learning.
+
+### 8.1 Speech recognition module
+
+The function of the speech recognition module is to generate output text based on the user's speech signals. The speech recognition module is composed of the following sub-functions: pre-processing, sound model learning, feature extraction, input/output management and language model learning sub-functions.
+
+#### 8.1.1 Pre-processing function
+
+The pre-processing function extracts a feature vector and removes noise from the noisy speech input. In this module, distributed noises with a high energy level and active noises with low energy level are removed to improve the quality of sound.
+
+#### 8.1.2 Sound model learning function
+
+The sound model learning functional entity produces a speaker independent acoustic model from a large speech database to recognize the general user's speech based on a deep neural network (DNN). This function also includes the process of building a speech database, and adaptation training for the specific speech environment, to make the speaker independent acoustic model optimal in the application environment. The sound model learning functional entity consists of a memory and a processor that generates sound-model state sets corresponding to multiple set training speech data. It then generates a multi-set state cluster from the sound-model state sets, and sets the multi-set training speech data as an input node, and the multi-set state cluster as an output node in order to learn a DNN structured parameter. When a user's speech and characteristic information are received by a user interface, the processor recognizes the user's speech on the basis of the learned DNN structured parameter by setting a sound-model state set corresponding to the characteristic information of the user's speech as an output node input/output management function.
+
+#### 8.1.3 Input/output management function
+
+The input/output management function provides the audio input interface function which processes the speech data input from the microphone, and the output interface function which recognizes speech data and sends back the recognition result to the user.
+
+#### 8.1.4 Language model learning function
+
+Language model learning functional entity performs training of word N-gram language model that defines the search network for continuous speech recognition. For language model training, text corpus of the recognition target should be prepared. The text corpus goes through a cleaning and refinement process first, and then language model training is performed on the clean text corpus. The language model is trained on the limited word list and the utterance dictionary is produced for the target word list. The language model database that stores a language model is used to convert the extracted feature vector into a text with a decoder.
+
+### 8.2 Natural language processing module
+
+The NLP module consists of a natural language understanding function and a linguistic knowledge learning/extraction function. The natural language understanding function is illustrated in Figure 5.
+
+It analyses the user's speech using the technologies of semantic level analysis such as semantic entity recognition and co-reference resolution, in addition to the well-known part-of-speech recognition, named entity (NE) recognition and syntactic analysis for sentence structures. The linguistic knowledge learning/extraction function extracts semantic relations among words and time/location information in the documents, and provides the framework to continuously acquire linguistic knowledge and to extend it to be able to deal with new knowledge. Natural language understanding function consists of a part-of-speech recognition sub-function, named entity recognition sub-function, syntactic analysis sub-function, semantic entity recognition sub-function and co-reference resolution sub-function. Learning and extraction of linguistic knowledge function is composed of semantic relation extraction sub-function, time/location information extraction sub-function and continuous linguistic knowledge acquisition and extension sub-function.
+
+
+
+```
+
+graph LR
+ A[POS analysis] --> B[NE analysis]
+ B --> C[Word sense recognition]
+ C --> D[Chunking]
+ D --> E[Dependency analysis]
+ E --> F[Semantic role labelling]
+
+```
+
+Flowchart of the Natural language understanding function showing a sequential process: POS analysis, NE analysis, Word sense recognition, Chunking, Dependency analysis, and Semantic role labelling.
+
+F.746.5(17)\_F05
+
+**Figure 5 – Natural language understanding function**
+
+### 8.3 Speech synthesis module
+
+Also known as text-to-speech (TTS) module, the speech synthesis module generates speech signals from the text input by text normalization and morphological analysis, intonation target (i.e., pitch contour) generation and speech signal generation using language analysis and intonation prediction information for the input sentences.
+
+### 8.4 Pronunciation fluency evaluation module
+
+The pronunciation fluency evaluation module evaluates the user's spontaneous speech input using the fluency feature model. The fluency evaluation consists of the analytic evaluation and the holistic evaluation for each evaluation item. The total scores of the analytic evaluation is the addition of each evaluation item score with different weights. The holistic evaluation is based on the impression of the fluency of the user by the evaluators. The final pronunciation fluency evaluation result is decided by selecting one of two evaluation methods.
+
+The pronunciation fluency evaluation is performed with the speech recognition module whereby the utterance verification function verifies the user's speech based on multi-event detection information and a predefined utterance verification model. To verify the user's utterance in a speech recognition system the following processes are used:
+
+- a noise processor configured to process the noise of an input speech signal;
+- a feature extractor configured to extract features of speech data obtained through the noise processing;
+- an event detector configured to detect events of the plurality of speech features occurring in the speech data using the noise-processed data and the data of the extracted features;
+- a decoder configured to perform speech recognition using a plurality of pre-set speech recognition models for the extracted feature data; and
+- an utterance verifier configured to calculate confidence measurement values in units of words and sentences using the information on the plurality of events detected by the event detector and a pre-set utterance verification model, and perform utterance verification according to the calculated confidence measurement values.
+
+The event detector includes a detector configured to detect features such as a noise level, a breathing sound, an interjection, a repetition of a phrase, hesitation, an exclamation, sound stretching, laughing, speech rate, and an incorrect pronunciation from the noise-processed data and the extracted feature data.
+
+The utterance verification model includes a word-level utterance verifier and sentence-level utterance verifier.
+
+The word-level utterance verifier calculates word-specific confidence scores of words of sections in which the events have occurred and words for which no event has occurred using the specific anti-model and the filler model pre-set in a database.
+
+The sentence-level event application utterance verifier calculates the confidence scores of the sentences using the statistical method, such as support vector machines (SVM) model, which has been pre-set in a database and trained by the statistical model such as SVM with training data reflecting a feature of a natural language. For sentence-level utterance verifier, the sentence structure and meaning analyser analyses the sentence structure and the meaning of the speech recognition result sentences using a morpheme analyser such as POS tagger and named entity analyser.
+
+### 8.5 Dialogue processing module
+
+The **dialogue processing module** performs dialogue act understanding function to express the dialogue intention/act of the utterances by analysing user's utterance strings and understanding their meaning.
+
+The **dialogue act training function** automatically trains dialogue patterns and statistical classification training information based on the domain dialogue corpus annotated with the dialogue acts to understand the participating user's intention.
+
+The **dialogue management function** analyses the n-best dialogue acts and meaning expressions and decides the best dialogue act, which is used to generate relevant system dialogue and manage the dialogue situations.
+
+The **dialogue generation function** selects the correct system response templet for the user's intention and decides meaningful information values to fill in the slots of the selected templet. Finally, it generates the appropriate system dialogue sentences.
+
+**Dialogue management and generation function** provides the following sub-functions:
+
+- **User intention analysis function**, to understand the user's intention correctly for the current topic
+- **Auxiliary topic handling function**, to provide responses if the topic is outside the main topic and guide the dialogue towards the appropriate topic flow
+- **Topic management knowledge search function**, to find relevant response patterns, slots or task knowledge to achieve the objective of the current topic
+- **Dialogue history management function**, to store changing tasks, slots and intentions and monitor the intention flows of the dialogue
+- **Next utterance recommendation function**, to suggest the next intention and utterances of the user according to the ongoing dialogue flow
+- **System reply generation function**, to provide responses according to the user's intention
+- **Dialogue management log record function**, to record the dialogue flow, the history change or search conditions. This log information is used to check the errors in the system and dialogue knowledge
+
+### 8.6 Dialogue understanding evaluation module
+
+The dialogue understanding evaluation module illustrated in Figure 6 evaluates the user's understanding of the ongoing topic by comparing user's utterances to the dialogue model of the system. It uses the dialogue understanding function and dialogue management function to search the dialogue knowledge. This function is part of the language learning module as an evaluation function. The system provides feedback, such as a better example to the user while evaluating the dialogue understanding to correct his responses.
+
+The response from the system differs according to the user's utterance determining if the topic is relevant or not. If the user's response contains grammatical errors or wrong expressions, the system provides the correct information for language learning purpose.
+
+The system guides the dialogue if the user responds with a different topic by restoring the ongoing topic of the dialogue. It can also change the topic to achieve the final goal of the dialogue and for the language learning purpose.
+
+
+
+```
+graph TD; A[User's utterance] --> B{Topic relevant?}; B -- No --> C[Dialogue processing]; B -- Yes --> D{dialogue flow correct?}; D -- No --> E[Dialogue processing]; D -- Yes --> F{grammatical error?}; F -- No --> G[Dialogue processing]; F -- Yes --> H{error feedback?}; H -- No --> G; H -- Yes --> G; subgraph C [Dialogue processing]; C1[Non topic response]; C2[Topic restoration]; C3[Error feedback]; end; subgraph E [Dialogue processing]; E1[Error feedback]; E2[Topic restoration]; end; subgraph G [Dialogue processing]; G1[Topic response]; G2[Error feedback]; G3[Topic response]; end;
+```
+
+Flowchart of the language learning by dialogue processing function. The process starts with 'User's utterance' and proceeds through a series of decision diamonds: 'Topic relevant?', 'dialogue flow correct?', 'grammatical error?', and 'error feedback?'. Each 'No' branch leads to a 'Dialogue processing' box containing specific responses like 'Non topic response', 'Topic restoration', or 'Error feedback'. Each 'Yes' branch leads to the next decision diamond. The final 'Yes' branch leads to a 'Topic response' box. The diagram is labeled F.746.5(17)\_F06.
+
+Figure 6 – Language learning by dialogue processing function
+
+### 8.7 Dialogue knowledge learning module
+
+The dialogue knowledge-learning module adds new dialogue knowledge in the dialogue management database by pseudo situation simulation and incremental learning of situation states. The sub-functions are automatic extraction function of conversation scenarios and incremental dialogue learning sub-functions.
+
+Automatic extraction of conversation scenarios sub-function: serves to collect big data dialogues among people from the scenarios of movies and dramas, and performs the speaker boundary recognition, relevance assessment and topic classification.
+
+Incremental dialogue learning sub-function: identifies the topic of the dialogue scenarios, augments with the slot information, intention and subjects according to the topic, and produces automatically or by human validation the dialogue knowledge that can be used for the dialogue system.
+
+### 8.8 Language learning module
+
+The language learning module, illustrated in Figure 7, takes the user's speech as input and automatically detects grammatical errors, corrects them and then sends the corrected sentence to the user as a feedback to improve his/her competence of foreign languages. The language-learning module consists of the grammatical error correction function and the expression learning function. The grammatical error correction function detects errors included in the user's spoken sentences and corrects them. On the other hand, the expression learning function provides feedback of the grammatical error and suggests better expressions to the user.
+
+- Grammatical error detection sub-function: detects grammatical errors in the user's spoken sentences. The grammatical errors are limited to those defined in the system. Multiple errors can be detected in one sentence. Various error detection models are used for the grammatical error detection.
+- Grammatical error correction sub-function: provides the correction information for detected grammatical errors. The error correction function produces grammatical error correction information by using the POS of the error words and context information around the words.
+- Error selection and correction sub-function: selects the best error candidate among those from different error detection models and generates error correction information on the selected candidate error.
+- Error feedback providing sub-function: informs the user of the grammatical errors and provides better expressions. The explicit/implicit error feedbacks are used accordingly depending on the situation of the error occurrences.
+
+
+
+```
+graph TD
+ Input --> ED1[Error detection by answer candidates]
+ Input --> ED2[Error detection by correction memory]
+ Input --> ED3[Dialogue base error detection]
+ Input --> ED4[Error detection by N-gram]
+ Input --> ED5[Error detection by machine learning]
+
+ ED1 --- KB1[(Answer set based error correction KB)]
+ ED2 --- EM1[(Error correction memory)]
+ ED3 --- DK1[(Dialogue context error correction knowledge)]
+ ED4 --- ND1[(N-gram data)]
+ ED5 --- GEDM1[(Grammatical error detection model)]
+
+ subgraph GED [Grammatical error detection]
+ ED1
+ ED2
+ ED3
+ ED4
+ ED5
+ KB1
+ EM1
+ DK1
+ ND1
+ GEDM1
+ end
+
+ GEDM1 --> CCG[Correction candidate generation]
+
+ subgraph GEC [Grammatical error correction]
+ CCG --> BCS([Best candidate selector])
+ BCS <--> LMV[LM based verification]
+ end
+
+ LMV --- LMD[(Language model DB)]
+
+ subgraph GEF [Grammatical error feedback]
+ BCS --> CFG[Correction feedback generation]
+ CFG <--> FC([Feedback controller])
+ GEDM2[(Grammatical error detection model)]
+ end
+```
+
+The flowchart illustrates the Language learning module's architecture. It begins with an 'Input' arrow pointing to five parallel error detection sub-functions: 'Error detection by answer candidates', 'Error detection by correction memory', 'Dialogue base error detection', 'Error detection by N-gram', and 'Error detection by machine learning'. Each sub-function is associated with a specific knowledge base or model: 'Answer set based error correction KB', 'Error correction memory', 'Dialogue context error correction knowledge', 'N-gram data', and 'Grammatical error detection model'. These five components are grouped under the label 'Grammatical error detection'. The output of the 'Error detection by machine learning' sub-function flows into 'Correction candidate generation'. This is followed by a 'Best candidate selector' (oval), which interacts bidirectionally with 'LM based verification'. The 'LM based verification' component is linked to a 'Language model DB'. The output of the 'Best candidate selector' flows into 'Correction feedback generation', which interacts bidirectionally with a 'Feedback controller' (oval). This final stage, including 'Correction feedback generation', 'Feedback controller', and a 'Grammatical error detection model', is grouped under the label 'Grammatical error feedback'.
+
+Flowchart of the Language learning module showing three main stages: Grammatical error detection, Grammatical error correction, and Grammatical error feedback.
+
+F.746.5(17)\_F07
+
+Figure 7 – Language learning module
+
+
+
+## SERIES OF ITU-T RECOMMENDATIONS
+
+| | |
+|-----------------|-----------------------------------------------------------------------------------------------------------------------------------------------------------|
+| Series A | Organization of the work of ITU-T |
+| Series D | Tariff and accounting principles and international telecommunication/ICT economic and policy issues |
+| Series E | Overall network operation, telephone service, service operation and human factors |
+| Series F | Non-telephone telecommunication services |
+| Series G | Transmission systems and media, digital systems and networks |
+| Series H | Audiovisual and multimedia systems |
+| Series I | Integrated services digital network |
+| Series J | Cable networks and transmission of television, sound programme and other multimedia signals |
+| Series K | Protection against interference |
+| Series L | Environment and ICTs, climate change, e-waste, energy efficiency; construction, installation and protection of cables and other elements of outside plant |
+| Series M | Telecommunication management, including TMN and network maintenance |
+| Series N | Maintenance: international sound programme and television transmission circuits |
+| Series O | Specifications of measuring equipment |
+| Series P | Telephone transmission quality, telephone installations, local line networks |
+| Series Q | Switching and signalling, and associated measurements and tests |
+| Series R | Telegraph transmission |
+| Series S | Telegraph services terminal equipment |
+| Series T | Terminals for telematic services |
+| Series U | Telegraph switching |
+| Series V | Data communication over the telephone network |
+| Series X | Data networks, open system communications and security |
+| Series Y | Global information infrastructure, Internet protocol aspects, next-generation networks, Internet of Things and smart cities |
+| Series Z | Languages and general software aspects for telecommunication systems |
\ No newline at end of file
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+
+
+International Telecommunication Union
+
+**ITU-T**
+
+TELECOMMUNICATION
+STANDARDIZATION SECTOR
+OF ITU
+
+**F.746.9**
+
+(05/2019)
+
+SERIES F: NON-TELEPHONE TELECOMMUNICATION
+SERVICES
+
+Multimedia services
+
+---
+
+**Requirements and architecture for indoor
+conversational robot systems**
+
+Recommendation ITU-T F.746.9
+
+ITU-T
+
+
+
+The logo of the International Telecommunication Union (ITU) features a globe with a red lightning bolt striking across it. To the right of the globe, the text "International Telecommunication Union" is written in blue, with "ITU" in a larger, bold font above it.
+
+ITU logo
+
+International
+Telecommunication
+Union
+
+# ITU-T F-SERIES RECOMMENDATIONS **NON-TELEPHONE TELECOMMUNICATION SERVICES**
+
+| | |
+|-----------------------------------------------------------------|--------------------|
+| TELEGRAPH SERVICE | |
+| Operating methods for the international public telegram service | F.1–F.19 |
+| The gentex network | F.20–F.29 |
+| Message switching | F.30–F.39 |
+| The international telemessage service | F.40–F.58 |
+| The international telex service | F.59–F.89 |
+| Statistics and publications on international telegraph services | F.90–F.99 |
+| Scheduled and leased communication services | F.100–F.104 |
+| Phototelegraph service | F.105–F.109 |
+| MOBILE SERVICE | |
+| Mobile services and multdestination satellite services | F.110–F.159 |
+| TELEMATIC SERVICES | |
+| Public facsimile service | F.160–F.199 |
+| Teletex service | F.200–F.299 |
+| Videotex service | F.300–F.349 |
+| General provisions for telematic services | F.350–F.399 |
+| MESSAGE HANDLING SERVICES | F.400–F.499 |
+| DIRECTORY SERVICES | F.500–F.549 |
+| DOCUMENT COMMUNICATION | |
+| Document communication | F.550–F.579 |
+| Programming communication interfaces | F.580–F.599 |
+| DATA TRANSMISSION SERVICES | F.600–F.699 |
+| MULTIMEDIA SERVICES | F.700–F.799 |
+| ISDN SERVICES | F.800–F.849 |
+| UNIVERSAL PERSONAL TELECOMMUNICATION | F.850–F.899 |
+| ACCESSIBILITY AND HUMAN FACTORS | F.900–F.999 |
+
+*For further details, please refer to the list of ITU-T Recommendations.*
+
+## Recommendation ITU-T F.746.9
+
+# Requirements and architecture for indoor conversational robot systems
+
+## Summary
+
+Recommendation ITU-T F.746.9 describes the requirements and architecture for an indoor conversational robot system. This Recommendation defines different functions to support indoor conversational robot systems. The scope of this Recommendation is focused on architecture, terminals, servers and interfaces between modules. It also describes different functions including a variable-distance speech preprocessing function, user identifying speech recognition function, multitask dialogue processing function and speech synthesis function. Additionally, it describes interfaces between modules for indoor conversational robot systems.
+
+## History
+
+| Edition | Recommendation | Approval | Study Group | Unique ID* |
+|---------|----------------|------------|-------------|---------------------------------------------------------------------------|
+| 1.0 | ITU-T F.746.9 | 2019-05-14 | 16 | 11.1002/1000/13916 |
+
+### Keywords
+
+AI robot, dialogue processing, speech interface
+
+---
+
+\* To access the Recommendation, type the URL in the address field of your web browser, followed by the Recommendation's unique ID. For example, .
+
+## FOREWORD
+
+The International Telecommunication Union (ITU) is the United Nations specialized agency in the field of telecommunications, information and communication technologies (ICTs). The ITU Telecommunication Standardization Sector (ITU-T) is a permanent organ of ITU. ITU-T is responsible for studying technical, operating and tariff questions and issuing Recommendations on them with a view to standardizing telecommunications on a worldwide basis.
+
+The World Telecommunication Standardization Assembly (WTSA), which meets every four years, establishes the topics for study by the ITU-T study groups which, in turn, produce Recommendations on these topics.
+
+The approval of ITU-T Recommendations is covered by the procedure laid down in WTSA Resolution 1.
+
+In some areas of information technology which fall within ITU-T's purview, the necessary standards are prepared on a collaborative basis with ISO and IEC.
+
+## NOTE
+
+In this Recommendation, the expression "Administration" is used for conciseness to indicate both a telecommunication administration and a recognized operating agency.
+
+Compliance with this Recommendation is voluntary. However, the Recommendation may contain certain mandatory provisions (to ensure, e.g., interoperability or applicability) and compliance with the Recommendation is achieved when all of these mandatory provisions are met. The words "shall" or some other obligatory language such as "must" and the negative equivalents are used to express requirements. The use of such words does not suggest that compliance with the Recommendation is required of any party.
+
+## INTELLECTUAL PROPERTY RIGHTS
+
+ITU draws attention to the possibility that the practice or implementation of this Recommendation may involve the use of a claimed Intellectual Property Right. ITU takes no position concerning the evidence, validity or applicability of claimed Intellectual Property Rights, whether asserted by ITU members or others outside of the Recommendation development process.
+
+As of the date of approval of this Recommendation, ITU had received notice of intellectual property, protected by patents, which may be required to implement this Recommendation. However, implementers are cautioned that this may not represent the latest information and are therefore strongly urged to consult the TSB patent database at .
+
+© ITU 2019
+
+All rights reserved. No part of this publication may be reproduced, by any means whatsoever, without the prior written permission of ITU.
+
+## Table of Contents
+
+###### Page
+
+| | | |
+|------------|------------------------------------------------------------------------------------------------------------------------------------|----|
+| 1 | Scope..... | 1 |
+| 2 | References..... | 1 |
+| 3 | Definitions ..... | 1 |
+| 3.1 | Terms defined elsewhere ..... | 1 |
+| 3.2 | Terms defined in this Recommendation..... | 1 |
+| 4 | Abbreviations and acronyms ..... | 2 |
+| 5 | Conventions ..... | 2 |
+| 6 | Introduction..... | 3 |
+| 6.1 | Basic concept of indoor conversational robot ..... | 3 |
+| 7 | Requirements of indoor conversational robot systems..... | 3 |
+| 8 | Functional components and interfaces for indoor conversational robot systems ..... | 4 |
+| 8.1 | Variable-distance speech preprocessing module..... | 5 |
+| 8.2 | User identifying speech recognition module..... | 7 |
+| 8.3 | Multitask dialogue processing module..... | 8 |
+| 8.4 | Speech synthesis module..... | 9 |
+| 9 | Application programme interfaces (API) for indoor conversational robot systems..... | 9 |
+| 9.1 | APIs to communicate between client and server..... | 9 |
+| 9.2 | APIs for preprocessing module ..... | 10 |
+| 9.3 | APIs for automatic speech recognition module..... | 11 |
+| 9.4 | APIs for dialogue module..... | 12 |
+| Appendix I | – Evaluation method for measuring performance of an indoor conversational robot system in variable distant noisy environments..... | 14 |
+| I.1 | Evaluation of speech recognition in variable distant noisy environments .... | 14 |
+| I.2 | Evaluation of call success in noisy environments ..... | 15 |
+| I.3 | Evaluation of conversations of specific purposes in indoor noisy environments ..... | 15 |
+| | Bibliography..... | 16 |
+
+
+
+# Requirements and architecture for indoor conversational robot systems
+
+# 1 Scope
+
+This Recommendation provides an overview of the framework for indoor conversational robot systems. It describes the features, general requirements, architecture and functionality, which are the framework to support indoor conversational robot systems. The scope is focused on architecture, terminals, servers, interface and communication protocols between servers and clients in a high-level approach. This Recommendation will allow users of the indoor conversational robot system to be able to experience convenient information services in various areas with a user-friendly speech-dialogue interface.
+
+# 2 References
+
+None.
+
+# 3 Definitions
+
+## 3.1 Terms defined elsewhere
+
+This Recommendation uses the following terms defined elsewhere:
+
+**3.1.1 co-reference resolution** [b-ITU-T F.746.3]: A function that detects the preceding referents of the pronouns which replace the noun phrases of the input sentences.
+
+**3.1.2 named entity recognition** [b-ITU-T F.746.3]: A function that recognizes named entities such as PLO which are people, organizations and places from the sentences. The PLO can be decomposed to more specific named entities depending on the applications.
+
+**3.1.3 natural language processing** [b-ITU-T F.746.3]: A method that analyses text in natural languages through several processes such as part-of- speech recognition, syntactic analysis and semantic analysis.
+
+**3.1.4 part-of-speech recognition** [b-ITU-T F.746.3]: A function that recognizes parts of speech (POS) in the sentences and assigns relevant POS tags considering contextual meaning of the target sentences.
+
+**3.1.5 semantic analysis** [b-ITU-T F.746.3]: A function that recognizes the semantic relations among the words around predicates that exist in the same sentence. The semantic analysis function then generates a semantic predicate-argument structure (PAS).
+
+**3.1.6 speech** [b-ITU-T H.703]: Speech is the vocalized form of human communication.
+
+**3.1.7 speech recognition** [b-ITU-T H.703]: A kind of user interface for translation of spoken words into text.
+
+**3.1.8 syntactic analysis** [b-ITU-T F.746.3]: A function that analyses sentence structures and generates dependency relations among words based on dependency grammars.
+
+## 3.2 Terms defined in this Recommendation
+
+This Recommendation defines the following terms:
+
+**3.2.1 dialogue-based speech interface**: An interface based on speech, especially dialogues between a user and a device or system.
+
+**3.2.2 dialogue act:** The user's intention or purpose of the utterances in a dialogue, for example, a request for information, command for action or agreement.
+
+# **4 Abbreviations and acronyms**
+
+This Recommendation uses the following abbreviations and acronyms:
+
+| | |
+|------|---------------------------------------------------------|
+| AI | Artificial Intelligence |
+| ASR | Automatic Speech Recognition |
+| DA | Dialogue Act |
+| DB | Database |
+| DNN | Deep Neural Network |
+| EER | Equal Error Rate |
+| FAR | False Alarm Rate |
+| FRR | False Rejection Rate |
+| HCI | Human Computer Interaction |
+| ICT | Information and Communication Technology |
+| IPTV | Internet Protocol Television |
+| IT | Information Technology |
+| LLS | Language Learning System based on speech/NLP technology |
+| LSTM | Long Short Term Memory |
+| NE | Named Entity |
+| NLP | Natural Language Processing |
+| PC | Personal Computer |
+| POS | Part Of Speech |
+| RT | Reverberation Time |
+| SMS | Short Message Service |
+| SNR | Signal to Noise Ratio |
+| SVM | Support Vector Machines |
+| TTS | Text To Speech |
+| VAD | Voice Activity Detection |
+| VoD | Video on Demand |
+
+# **5 Conventions**
+
+The following conventions are used in this Recommendation:
+
+- The keywords "is required to" indicate a requirement that must be strictly followed and from which no deviation is permitted, if conformance to this Recommendation is to be claimed.
+- The keywords "is prohibited from" indicate a requirement that must be strictly prohibited, if conformance to this Recommendation is to be claimed.
+- The keywords "is recommended" indicate a requirement that is recommended but which is not absolutely required. Thus, this requirement need not be present to claim conformance.
+
+- The keywords "is not recommended" indicate a requirement that is not recommended but which is not specifically prohibited. Thus, conformance with this Recommendation can still be claimed even if this requirement is present.
+- The keywords "can optionally" indicate an optional requirement that is permissible, without implying any sense of being recommended. This term is not intended to imply that the vendor's implementation must provide the option and the feature can be optionally enabled by the network operator/service provider. Rather, it means the vendor may optionally provide the feature and still claim conformance with this Recommendation.
+
+# 6 Introduction
+
+These days the application of artificial intelligence (AI) technology has expanded further into areas such as robotics. Indoor conversational robot systems are one of the AI applications equipped with speech interfaces that enable users to have a dialogue with robots. The key technologies in such a multimedia system are speech recognition technology for variable distance speech and multitask dialogue processing technology which analyses the resulting natural language text from the speech recognition, understands the meaning of the spoken dialogues and generates the best relevant responses. In this way, the intelligent robot can perform the service for the human user while having a conversation with him/her.
+
+The indoor conversational robot can be applied to various areas. It can serve people as a kiosk robot to guide customers or to introduce different services in the private and public sectors. It can also serve as a conversational helper for everyday life for individuals living alone, e.g. an elderly person. It can provide people with recipes through question and answer speech dialogues. It can be used as a personal assistant robot to manage a schedule. The last use-case example is a robot guide which provides dialogue-based information service on domestic multimedia content such as that for Internet Protocol TV (IPTV) or video on demand (VoD).
+
+In this document, we present the requirements, architecture and functions for indoor conversational robot systems.
+
+## 6.1 Basic concept of indoor conversational robot
+
+An indoor conversational robot is a type of intelligent agent that has the capability to have a dialogue with people in a room. The purpose of the dialogue between a robot and people is for the robot to provide various services to people. To provide such intelligent services the core technologies include variable-distance speech recognition and multitask dialogue processing technology. The robot should first be able to recognize speech spoken by a person in a noisy room who may walk around. It means the distance of the speech recognition target is not determined but variable. After the speech recognition is successful, the robot then should be able to understand the result of the speech recognition that is in text form. It should process the text that is in a natural language to find the meaning of the speech in terms of different task dimensions. It also performs the dialogue processing by dialogue management and dialogue status tracking techniques to find out the speaker's intention and purpose of the dialogue while adapting to the speaker's conversational style. In the long run, the robot, or the intelligent agent achieves his goal by providing the appropriate service after figuring out the conversation.
+
+# 7 Requirements of indoor conversational robot systems
+
+The general requirements for an indoor conversational robot system (ICR) are described as follows.
+
+- An ICR is required to provide a speech recognition function for spontaneous speech.
+- An ICR is required to be able to recognize the predefined activation command spoken by the user.
+
+- An ICR is recommended to provide a keyword registration function for the user.
+- An ICR is recommended to provide a dialogue processing function for spontaneous utterances.
+- An ICR is recommended to be able to understand the user's intention by analysing the speaker's speech acts.
+- An ICR is recommended to provide a conversation tracking function to understand the interactive dialogues between the user and the system.
+- An ICR is recommended to provide a dialogue generation function to perform the interactive dialogues between the user and the system.
+- An ICR is recommended to be able to identify pre-validated users.
+- An ICR is recommended to be able to recognize the location of the user and change its position towards the user.
+- An ICR is recommended to be able to identify pre-validated users, recognize the location of the users and the predefined activation command at the same time.
+- An ICR is recommended to recognize speech in the noisy environment with reverberation.
+- An ICR is recommended to process dialogues demanding multiple tasks.
+- An ICR is recommended to be able to adapt to the user through conversational experiences through incremental learning.
+
+# **8 Functional components and interfaces for indoor conversational robot systems**
+
+The functional components of indoor conversational robot systems, presented in Figure 1, are composed of the following modules:
+
+- variable-distance speech preprocessing module;
+- user identifying speech recognition module;
+- multitask dialogue processing module;
+- speech synthesis module (TTS: text to speech).
+
+
+
+F.746.9(19)\_F01
+
+Figure 1: Indoor conversational robot system architecture diagram. The diagram shows a User (represented by a person icon) and a ROBOT (represented by a cloud icon). The User sends speech input (e.g., 'Romeo, where are you Romeo?', 'Tony, what's the traffic like on the way to the shopping centre?', 'Albert, you'd better take a bus, and you need to be back for a meeting at 2.') which is affected by noise, reverberation, and distance. The speech is processed by a Variable-distance speech preprocessing module (containing Beam forming, Sound separation, and Noise reverberation removal). The output is then processed by a User identifying speech recognition module (containing Keyword, Speaker, and Speech recognition). The result is sent to a Multi-task dialogue processing module (containing Dialogue generation, Semantic analysis, Dialogue manager, and Dialogue state tracking). The Dialogue manager interacts with a Web cloud. The output of the Dialogue manager is processed by a TTS (Text-to-Speech) module, which generates the robot's response (e.g., 'Albert, you'd better take a bus, and you need to be back for a meeting at 2.'). The User is labeled as 'Variable-distance indoor noise/reverberation'.
+
+**Figure 1 – Indoor conversational robot system**
+
+In the variable-distance speech preprocessing module, various reverberations of the indoor environments and noise inflicted variable-distance speech is cleaned and the reliable speech recognition is made possible.
+
+In the user identifying speech recognition module, the pre-validated user calls the robot with predefined words which is waiting for a command. The robot is then activated, recognizes the specific user and starts a dialogue with the user.
+
+In the multitask dialogue processing module, the robot understands the information in the natural language text which is the speech recognition result. The robot has the conversation with the user by adaptive dialogue management, generates responses and expands or changes the dialogue topic appropriately depending on the different tasks.
+
+In the speech synthesis module, the result of the dialogue generation turns into the sound of the robot. That is the well-known text-to-speech module in the general speech interface.
+
+
+
+F.746.9(19)\_F02
+
+Figure 2: Functional architecture of indoor conversational robot system. This is a linear flow diagram showing four sequential steps: Speech preprocessing, Speech recognition, Dialogue processing, and Speech synthesis. The steps are connected by arrows from left to right.
+
+**Figure 2 – Functional architecture of indoor conversational robot system**
+
+## 8.1 Variable-distance speech preprocessing module
+
+In the variable-distance speech preprocessing module, various reverberations of the indoor environments and noise inflicted variable-distance speech is cleaned and the reliable speech recognition is made possible. The following functions are included in the variable-distance speech preprocessing module as essential functions:
+
+- Sound localization function that is robust for reverberation – This function detects the direction of the sound source with noise and reverberation;
+- Noise reverberation-removing function – This function removes or minimizes noise and reverberations from the sound source using methods such as the beamforming algorithm that keeps the direction information and minimizes noise from the sound. Reverberation suppression is performed which is independent of the array structure of the microphone.
+- Sound separation function – This function separates voice features from multichannel input sound signal information of frequency, time and channel to remove background noise. The resulting voice signal proceeds to a speech recognizer as the input signal.
+- Sound feature compensation function – This function changes from distorted voice feature to clean voice feature using inference by deep neural network (DNN) sound modelling for better speech recognition.
+
+For reliable variable-distance speech recognition, the database (DB) information on the items in the following table is required.
+
+**Table 1 – Database information for variable-distance speech recognition for indoor conversational robot system**
+
+| DB information type | Information subtype | Example |
+|----------------------------|-------------------------------------|------------------------------------|
+| Language information | | |
+| | Language type | English, French, Korean |
+| Speaker information | | |
+| | Gender | Male, Female |
+| | Age | 17, 25, 60th, 30th |
+| | Origin | Macao, Italy, Southern France |
+| Room acoustic information | | |
+| | Surrounding noise type | Point noise source/ambient noise |
+| | Noise type | Music, babble |
+| | Speech-to-noise ratio | 100 vs. 1 |
+| Microphone information | | |
+| | Model name | MT600 |
+| | Type of microphone | Dynamic, condenser, mems |
+| | Channel type | Single/multiple |
+| | Number of microphones | |
+| | Microphone array configuration type | linear, circular |
+| Speech information | | |
+| | Location of the speaker | Distance and angle from microphone |
+| | Speech contents | Words, linked words, sentences |
+| | Speech style | Reading, spontaneous |
+| File information | | |
+| | File type | Raw, wav |
+| | Sampling rate | 8 kHz, 16 kHz, 44.1 kHz, 48 kHz |
+| | File name structure | Speech1-raw-16 kHz |
+
+## 8.2 User identifying speech recognition module
+
+The user identifying speech recognition module performs the following processes: the pre-validated user calls the robot with predefined words which is waiting for a command. The robot is then activated, recognizes the specific user, and starts a dialogue with the user. The function of the speech recognition module is to generate output text from the user's speech signals. The following functions are used for the user identifying speech recognition module.
+
+- Speech DB construction – This function, for the indoor home environment, variable distance multichannel speech DB collection, is needed using microphone arrays for the speech recognition module. The collected speech utterances is arranged to include silent sections for end-point detection.
+
+
+
+The diagram illustrates a multichannel microphone array speech DB collection system. On the left, a 'Multichannel mic array' is shown, consisting of a circular base with multiple microphones arranged around it. Arrows point from the microphones to a 'Multichannel amplifier' in the center, which is a rack-mounted unit with many small black modules. From the amplifier, arrows point to a 'USB interface' unit, which is a small white device with several ports. Finally, an arrow points from the USB interface to a 'PC for multichannel recording', which is a desktop computer with a monitor displaying a landscape image.
+
+Diagram of a multichannel microphone array speech DB collection system. The system consists of a multichannel mic array connected to a multichannel amplifier, which is connected to a USB interface, which is connected to a PC for multichannel recording.
+
+F.746.9(19)\_F03
+
+**Figure 3 – Example of multichannel microphone array speech DB collection system**
+
+- End-point detection function – This function detects the voice signal from the input signal. This function is used as a preprocess for speech recognition, speaker verification or speaker identification. It consists of voice activity detection (VAD) stage and smoothing stage. Voice activity detection (VAD) is to classify the input signal into voice and non-voice using DNN. The result of VAD is run through a smoothing process by a hangover technique and returns the end-point of each sentence.
+- Keyword extraction function – This function, which utilizes a DNN sound model, is robust against background noise. Keywords are registered by the user for activating robots and used as training data for keyword extraction and speech recognition.
+- Speaker identification function – This function, which utilizes DNN feature analysis, is robust against background noise. Speaker identification is a type of classification task to detect a speaker of the utterance from a certain speaker group. Recent AI technologies such as DNN improves the performance of classification tasks.
+- Automatic speech recognition function (ASR) – This function generates output text from the user's speech signals. The ASR function should be scalable to multi-robot environments as the example architecture in Figure 4 shows. Training data for ASR is composed of that recorded in similar environments with noise and variable distance.
+
+
+
+Diagram of a speech interface for multiple conversational robots. On the left, three user silhouettes are shown with speech waveforms. The top user has a microphone icon, the middle user has a red ear icon, and the bottom user has a computer monitor icon. Arrows labeled 'PCM' and 'N-best results' point from these users to a central 'Load balancer' (represented by a server icon with a database symbol). The load balancer has arrows pointing to three 'Speech recognizer' units (represented by server icons). A 'Client' icon (microphone) is also shown with an arrow pointing to the load balancer. The diagram is labeled 'F.746.9(19)\_F04' in the bottom right corner.
+
+F.746.9(19)\_F04
+
+**Figure 4 – Speech Interface for multiple conversational robots**
+
+The user identifying speech recognition module employs the deep neural network (DNN) model in most functions in the module. In general, a deep neural network (DNN) model shows good performance in the generation or classification task. However, DNN fundamentally has non-linear characteristics, and therefore it is difficult to interpret how a result from inputs given to a black box model has been derived. To explain the hidden process, a linear approximation of a DNN model which is a non-linear function is performed with the following operations consecutively: an operation of expanding an input to a neuron of the DNN into a polynomial; a second operation of approximating the neuron of the DNN with a Taylor series in parallel with the polynomial expansion of the input; and a third operation of classifying the polynomially-expanded input and the Taylor-series approximated neuron as a polynomial of input signals and a polynomial of weights.
+
+## 8.3 Multitask dialogue processing module
+
+The multitask dialogue processing module performs the following functions: the robot understands the information in the natural language text which is the speech recognition result. The robot has the conversation with the user by adaptive dialogue management, generates responses and expands or changes the dialogue topic appropriately depending on the different tasks. The following functions are included in the multitask dialogue processing module.
+
+- Semantic analysis of dialogues – Semantic analysis is the essential function for understanding the user's intention of the utterance. It should be capable of multitask semantic tagging which is used for the analysis. Speech act and dialogue act analysis models are employed for the dialogue understanding function. A slot filling model for dialogue understanding is constructed based on DNN using a large corpus of user dialogues. Dialogue topic expansion and modification to improve the dialogue model are also included in the semantic analyser function.
+- Dialogue state tracking function – This function detects the state of each turn of the user/robot dialogue such as "question", "answer" or "making commands" which are robust for dialogue topic expansion and modification. DNN-based dialogue state tracking technology is used for dialogue state recognition. In Figure 5 an example dialogue state tracker is presented which uses long short-term memory (LSTM) networks, a recently developed neural network.
+
+
+
+Diagram of a dialogue state tracker architecture. It shows a sequence of four LSTM units. Each unit receives a 'Dialogue-act list' as input at time steps t=1, t=2, t=3, and t=L. Each LSTM unit outputs a 'Goal label'. The units are connected sequentially from left to right.
+
+F.746.9(19)\_F05
+
+**Figure 5 – Example of dialogue state tracker**
+
+- Dialogue management function – This function manages the dialogue between the user and the robot based on the intention of the user. The dialogue management function should be capable of expanding and modifying dialogue topics. Various reinforcement learning methods based on DNN are employed for better performance of dialogue management.
+- Dialogue generation function – This function produces a robot utterance with a correct dialogue act from the input dialogue act of the human user. Based on a statistical model the dialogue generation function is task adaptable for multiple dialogue topics.
+
+## **8.4 Speech synthesis module**
+
+The speech synthesis module performs the following functions: the result of the dialogue generation turns into the sound of the robot. This is the well-known text-to-speech module in the general speech interface. The speech synthesis module generates speech signals from the text input by text normalization and morphological analysis, intonation target (i.e., pitch contour) generation and speech signal generation using language analysis and intonation prediction information for the input sentences.
+
+# **9 Application programme interfaces (API) for indoor conversational robot systems**
+
+In this clause, APIs for different modules of a robot system are defined: communication between client and server, preprocessing module, speech recognition module and dialogue processing module.
+
+## **9.1 APIs to communicate between client and server**
+
+The APIs to communicate between the client and server consists of methods to make a new connection to the server, to recognize recorded multichannel signals, to get an ASR or dialogue result for a given input signal and to get a response from the robot to the current user input in wave format.
+
+**Table 2 – APIs for communication between server and client**
+
+| | |
+|-----------------------------|----------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+| Constructor | |
+| Constructor and description | |
+| ConversationalRobot() | |
+| Default constructor | |
+| Methods | |
+| Modifier and type | Method and description |
+| int | openConnection(String id, String ipAddress, Integer port) |
+| | Make a new connection to ASR/dialogue server
id: Unique identifier of client
ipAddress: ip address of ASR/Dialogue server
port: TCP port number to connect server |
+
+**Table 2 – APIs for communication between server and client**
+
+| | |
+|-----------------|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+| | Returns 0 on success or ERROR code otherwise |
+| void | closeConnection() |
+| int | setParameters(String key, String value)
Set control parameters of either client or server including number of channels, kind of input signal, domain of conversation etc
key: parameter name
value: parameter value
Returns 0 on success or ERROR code otherwise |
+| String | getParameters(String key)
Get control parameters of either client or server
key: parameter name
Returns value corresponding to key |
+| int | Recognize(Array> sig, int dim, int len)
Recognize recorded multichannel signal
dim: number of microphone channels
len: length of signal
Returns status of recognizer |
+| String | getResult(int kind)
Get ASR or dialogue result for given input signal so far
kind: kind of result: ASR or Dialogue
Returns result of ASR, dialogue, etc in text format |
+| Array | getResponse()
Get response of robot to current user input in wave format, if any
Returns waveform data which can be played in |
+| String | getStatus(int kind)
Get current status of ASR or dialogue system
kind: kind of status
Returns the current status of engine in text format |
+
+## 9.2 APIs for preprocessing module
+
+The APIs for the preprocessing module creates resources for the preprocessing and processing of a block of multichannel audio signals for the use of speech recognition in the next step.
+
+**Table 3 – APIs for preprocessing module**
+
+| | |
+|-----------------------------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+| Constructor | |
+| Constructor and description | |
+| CPreproc() | |
+| Default constructor | |
+| Methods | |
+| Modifier and type | Method and description |
+| int | createPreproc(int ch, int fs)
Create resources for preprocessing
ch: number of channels
fs: sampling frequency of input signal
Returns 0 on success, error code otherwise |
+
+**Table 3 – APIs for preprocessing module**
+
+| | |
+|--------|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+| void | freePreproc()
Free allocated resources |
+| int | processBlock(Array> insig, int len, Array& outsig)
Preprocess a block of muti-channel audio signals
insig: multichannel speech signals
len: length of input signals
outsig: output single channel signal
Returns length of output signals |
+| int | setParameters(String key, String value)
Set control parameters of preprocessing module
key: parameter name
value: parameter value
Returns 0 on success or error code otherwise |
+| String | getParameters(String key)
Get control parameters of preprocessing module
key: parameter name
Returns value corresponding to the key |
+
+## 9.3 APIs for automatic speech recognition module
+
+This module includes key-word spotting, speaker identification, language identification and speech recognition. It returns result of the ASR module in a text format. The result can have more than one hypothesis.
+
+**Table 4 – APIs for ASR module**
+
+| | |
+|-----------------------------|--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+| Constructor | |
+| Constructor and description | |
+| CASR() | |
+| Default constructor | |
+| Methods | |
+| Modifier and type | Method and description |
+| int | createASR(int ch, int fs)
Create resources for ASR
ch: number of channels
fs: sampling frequency of input signal
Returns 0 on success, error code otherwise |
+| void | freePreproc()
Free allocated resources |
+| int | processBlock(Array> insig, int len)