---
license: other
language: [hi, mr, ne, mai, sa, brx, kok, doi, gu, pa, or, ta, te, kn, ml, mni, bn, as, ur, sd, ks, sat]
tags: [transliteration, code-mixing, text-to-speech, indic]
---
# indictrans: English words in Indian-language text, written in the request's script

Runtime assets of the code-mix transliteration layer of the Finesse TTS (`utils/codemix_xlit`):
English words inside Indic text are rewritten in the language's script, spelled the way an
Indian-English speaker says them, so an Indic voice reads them correctly; text typed entirely in
Latin is read word by word, the language's own words back into its script. 22 languages (Dogri and
Santali through the Hindi model).

Version 1.3.0+c0ad24b04aaa. Built by `tools/codemix_xlit/build_assets.py`; `manifest.json` lists every file
with its size and SHA-256.

## Contents
- `model/`: the IndicXlit en->indic v1.0 transformer converted to CTranslate2
- `lexicon/<code>.reviewed.json`, `lexicon/<code>.generated.json`: reviewed and generated spellings
- `rescore/`: pruned IndicXlit word-frequency dictionaries
- `cmudict.json`, `english_*`: English pronunciations, vocabulary and reviewed corrections
- `indic_words.json`: Indian words read natively; `ranker.json`: candidate ranker
- `roman/<code>.json`: how people type each language's words in Latin, and how often

## Sources and licences
- IndicXlit model and word-frequency dictionaries: AI4Bharat, MIT licence
  (https://github.com/AI4Bharat/IndicXlit)
- CMU Pronouncing Dictionary: Carnegie Mellon University, BSD-style licence
- English word lists derived from wordfreq (https://github.com/rspeer/wordfreq): CC BY-SA 4.0
- Dakshina dataset (Roark et al. 2020, https://github.com/google-research-datasets/dakshina):
  CC BY-SA 4.0; the romanized tables of bn, gu, hi, kn, ml, mr, pa, sd, ta, te, ur use counts
  derived from its romanized sentences, and those tables are shared under CC BY-SA 4.0
- Lexicons, corrections, ranker and the other romanized tables: derived from the above and reviewed