BharatBhasha AI - Text-to-Speech (TTS) Models Catalog

📌 Repository Purpose & Motivation

This repository provides dedicated neural voice synthesis models, VITS checkpoints, and phonetic assets supporting natural offline voice synthesis across all 22 Official Scheduled Indian Languages + English.

Why this repository exists:

Un-gated Direct Distribution: Eliminates gating screens, Hugging Face login prompts, or token requirements so mobile (Android) and desktop apps can fetch voices seamlessly.
Hybrid Multi-Engine Architecture: Provides both dedicated lightweight ONNX models (Piper Neural Voices, ~60 MB) for major languages, and high-coverage VITS models (Meta MMS, ~140 MB) for regional languages.
Phonetic Independence: Bundles the complete espeak-ng-data database and phonetic dictionaries for regional languages (e.g. Sanskrit, Bodo, Santali) so apps operate 100% offline without external system dependencies.

🏗️ Repository Folder Structure

remiai3/TTS_MODELS_FOR_APP/
├── .gitattributes
├── README.md                                          # Documentation & Catalog
│
├── espeak-ng-data/                                    # Universal Phonetic Rules & Tables (17 MB)
│   ├── phontab, phonindex, phondata
│   └── voices/ (all phonetic tables)
│
├── [Piper Neural Voice ONNX Models & Configs]         # Ultra-Fast ONNX Voices (~60 MB each)
│   ├── hi_IN-pratham-medium.onnx (.json)              # Hindi
│   ├── te_IN-maya-medium.onnx (.json)                 # Telugu
│   ├── bn_BD-google-medium.onnx (.json)               # Bengali
│   ├── en_US-lessac-medium.onnx (.json)               # English
│   ├── mr_IN-google-medium.onnx (.json)               # Marathi
│   ├── ml_IN-arjun-medium.onnx (.json)                # Malayalam
│   ├── ne_NP-google-medium.onnx (.json)               # Nepali
│   └── ur_PK-fasih-medium.onnx (.json)                # Urdu
│
├── [Meta MMS VITS Models]                             # VITS Neural Voice Checkpoints (~140 MB each)
│   ├── mms_tts_tam/ (Tamil)                           # model.safetensors, config.json, vocab.json
│   ├── mms_tts_asm/ (Assamese)                        # model.safetensors, config.json, vocab.json
│   ├── mms_tts_guj/ (Gujarati)                        # model.safetensors, config.json, vocab.json
│   ├── mms_tts_kn/ (Kannada)                          # model.safetensors, config.json, vocab.json
│   ├── mms_tts_or/ (Odia)                             # model.safetensors, config.json, vocab.json
│   ├── mms_tts_doi/ (Dogri)                           # model.safetensors, config.json, vocab.json
│   └── mms_tts_mai/ (Maithili)                        # model.safetensors, config.json, vocab.json
│
└── [Indic Voice Phonetic Dictionaries]                # Lexical and phonetic assets
    ├── voice_tts_brx/ (Bodo)                          # model_info.json, brx_dict
    ├── voice_tts_kok/ (Konkani)                       # model_info.json, kok_dict
    ├── voice_tts_mni/ (Manipuri)                      # model_info.json, mni_dict
    ├── voice_tts_sa/ (Sanskrit)                       # model_info.json, sa_dict
    ├── voice_tts_sat/ (Santali)                       # model_info.json, sat_dict
    └── voice_tts_sd/ (Sindhi)                         # model_info.json, sd_dict

🌐 Direct Download Endpoints for Android & Mobile Apps

Clients can download individual voices on demand:

1. Piper Neural ONNX Voices & JSONs

https://huggingface.co/remiai3/TTS_MODELS_FOR_APP/resolve/main/{VOICE_FILENAME}.onnx
https://huggingface.co/remiai3/TTS_MODELS_FOR_APP/resolve/main/{VOICE_FILENAME}.onnx.json

Examples:

https://huggingface.co/remiai3/TTS_MODELS_FOR_APP/resolve/main/hi_IN-pratham-medium.onnx
https://huggingface.co/remiai3/TTS_MODELS_FOR_APP/resolve/main/te_IN-maya-medium.onnx

2. Meta MMS VITS Models

https://huggingface.co/remiai3/TTS_MODELS_FOR_APP/resolve/main/{MODEL_DIR}/model.safetensors
https://huggingface.co/remiai3/TTS_MODELS_FOR_APP/resolve/main/{MODEL_DIR}/config.json

Example for Tamil:

https://huggingface.co/remiai3/TTS_MODELS_FOR_APP/resolve/main/mms_tts_tam/model.safetensors
https://huggingface.co/remiai3/TTS_MODELS_FOR_APP/resolve/main/mms_tts_tam/config.json

📊 Complete TTS Voice Inventory

Language Code	Language	Voice Engine	Model Filename / Directory	Size	RAM Overhead
`hi`	Hindi	Piper ONNX	`hi_IN-pratham-medium.onnx`	60 MB	< 100 MB
`te`	Telugu	Piper ONNX	`te_IN-maya-medium.onnx`	60 MB	< 100 MB
`bn`	Bengali	Piper ONNX	`bn_BD-google-medium.onnx`	73 MB	< 100 MB
`en`	English	Piper ONNX	`en_US-lessac-medium.onnx`	60 MB	< 100 MB
`mr`	Marathi	Piper ONNX	`mr_IN-google-medium.onnx`	73 MB	< 100 MB
`ml`	Malayalam	Piper ONNX	`ml_IN-arjun-medium.onnx`	60 MB	< 100 MB
`ne`	Nepali	Piper ONNX	`ne_NP-google-medium.onnx`	73 MB	< 100 MB
`ur`	Urdu	Piper ONNX	`ur_PK-fasih-medium.onnx`	60 MB	< 100 MB
`ta`	Tamil	Meta MMS VITS	`mms_tts_tam`	138 MB	< 200 MB
`as`	Assamese	Meta MMS VITS	`mms_tts_asm`	138 MB	< 200 MB
`gu`	Gujarati	Meta MMS VITS	`mms_tts_guj`	138 MB	< 200 MB
`kn`	Kannada	Meta MMS VITS	`mms_tts_kn`	138 MB	< 200 MB
`or`	Odia	Meta MMS VITS	`mms_tts_or`	138 MB	< 200 MB
`doi`	Dogri	Meta MMS VITS	`mms_tts_doi`	138 MB	< 200 MB
`mai`	Maithili	Meta MMS VITS	`mms_tts_mai`	138 MB	< 200 MB
`brx`	Bodo	Indic-TTS Dict	`voice_tts_brx`	< 1 MB	< 50 MB
`kok`	Konkani	Indic-TTS Dict	`voice_tts_kok`	< 1 MB	< 50 MB
`mni`	Manipuri	Indic-TTS Dict	`voice_tts_mni`	< 1 MB	< 50 MB
`sa`	Sanskrit	Indic-TTS Dict	`voice_tts_sa`	< 1 MB	< 50 MB
`sat`	Santali	Indic-TTS Dict	`voice_tts_sat`	< 1 MB	< 50 MB
`sd`	Sindhi	Indic-TTS Dict	`voice_tts_sd`	< 1 MB	< 50 MB

⚖️ Open Source Licensing & Credits

Piper Neural Voices: Piper by Michael Hansen (Rhasspy) and contributors. Licenses: MIT / CC BY 4.0 / Public Domain (model dataset dependent).
Meta MMS VITS Models: Meta Massively Multilingual Speech by Meta AI Research. License: CC-BY-NC 4.0 (Creative Commons Attribution-NonCommercial 4.0).
Indic Voice Phonetic Dictionaries: AI4Bharat Indic-TTS by AI4Bharat (IIT Madras). License: MIT License.
eSpeak-NG: eSpeak-NG multi-lingual speech synthesizer. License: GPL-3.0.

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