Instructions to use remiai3/TTS_MODELS_FOR_APP with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Piper
How to use remiai3/TTS_MODELS_FOR_APP with Piper:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
- Google Colab
- Kaggle
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Download README.md from remiai3/TTS_MODELS_FOR_APP: direct link, hf CLI and curl.
- Browser
- Download file 7.27 kB
-
https://huggingface.co/remiai3/TTS_MODELS_FOR_APP/resolve/main/README.md
- Command line
-
hf download hf://remiai3/TTS_MODELS_FOR_APP/README.md
-
curl -L -o README.md https://huggingface.co/remiai3/TTS_MODELS_FOR_APP/resolve/main/README.md
7.27 kB
| license: cc-by-nc-4.0 | |
| language: | |
| - hi | |
| - bn | |
| - te | |
| - ta | |
| - mr | |
| - gu | |
| - kn | |
| - ml | |
| - pa | |
| - or | |
| - as | |
| - ur | |
| - sa | |
| - ne | |
| - kok | |
| - mai | |
| - brx | |
| - doi | |
| - ks | |
| - mni | |
| - sat | |
| - sd | |
| - en | |
| tags: | |
| - audio | |
| - text-to-speech | |
| - tts | |
| - piper | |
| - vits | |
| - mms | |
| - onnx | |
| - indic | |
| pipeline_tag: text-to-speech | |
| # BharatBhasha AI - Text-to-Speech (TTS) Models Catalog | |
| ## π 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: | |
| 1. **Un-gated Direct Distribution**: Eliminates gating screens, Hugging Face login prompts, or token requirements so mobile (Android) and desktop apps can fetch voices seamlessly. | |
| 2. **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. | |
| 3. **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. | |
| --- | |
| ## ποΈ Repository Folder Structure | |
| ```text | |
| remiai3/TTS_MODELS_FOR_APP/ | |
| βββ .gitattributes | |
| βββ README.md # Documentation & Catalog | |
| β | |
| βββ espeak-ng-data/ # Universal Phonetic Rules & Tables (17 MB) | |
| β βββ phontab, phonindex, phondata | |
| β βββ voices/ (all phonetic tables) | |
| β | |
| βββ [Piper Neural Voice ONNX Models & Configs] # Ultra-Fast ONNX Voices (~60 MB each) | |
| β βββ hi_IN-pratham-medium.onnx (.json) # Hindi | |
| β βββ te_IN-maya-medium.onnx (.json) # Telugu | |
| β βββ bn_BD-google-medium.onnx (.json) # Bengali | |
| β βββ en_US-lessac-medium.onnx (.json) # English | |
| β βββ mr_IN-google-medium.onnx (.json) # Marathi | |
| β βββ ml_IN-arjun-medium.onnx (.json) # Malayalam | |
| β βββ ne_NP-google-medium.onnx (.json) # Nepali | |
| β βββ ur_PK-fasih-medium.onnx (.json) # Urdu | |
| β | |
| βββ [Meta MMS VITS Models] # VITS Neural Voice Checkpoints (~140 MB each) | |
| β βββ mms_tts_tam/ (Tamil) # model.safetensors, config.json, vocab.json | |
| β βββ mms_tts_asm/ (Assamese) # model.safetensors, config.json, vocab.json | |
| β βββ mms_tts_guj/ (Gujarati) # model.safetensors, config.json, vocab.json | |
| β βββ mms_tts_kn/ (Kannada) # model.safetensors, config.json, vocab.json | |
| β βββ mms_tts_or/ (Odia) # model.safetensors, config.json, vocab.json | |
| β βββ mms_tts_doi/ (Dogri) # model.safetensors, config.json, vocab.json | |
| β βββ mms_tts_mai/ (Maithili) # model.safetensors, config.json, vocab.json | |
| β | |
| βββ [Indic Voice Phonetic Dictionaries] # Lexical and phonetic assets | |
| βββ voice_tts_brx/ (Bodo) # model_info.json, brx_dict | |
| βββ voice_tts_kok/ (Konkani) # model_info.json, kok_dict | |
| βββ voice_tts_mni/ (Manipuri) # model_info.json, mni_dict | |
| βββ voice_tts_sa/ (Sanskrit) # model_info.json, sa_dict | |
| βββ voice_tts_sat/ (Santali) # model_info.json, sat_dict | |
| βββ voice_tts_sd/ (Sindhi) # model_info.json, sd_dict | |
| ``` | |
| --- | |
| ## π Direct Download Endpoints for Android & Mobile Apps | |
| Clients can download individual voices on demand: | |
| ### 1. Piper Neural ONNX Voices & JSONs | |
| ```text | |
| 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 | |
| ```text | |
| 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` | |
| --- | |
| ## π 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 | | |
| --- | |
| ## βοΈ Open Source Licensing & Credits | |
| - **Piper Neural Voices**: [Piper](https://github.com/rhasspy/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](https://github.com/facebookresearch/fairseq/tree/main/examples/mms) by **Meta AI Research**. License: **CC-BY-NC 4.0** (Creative Commons Attribution-NonCommercial 4.0). | |
| - **Indic Voice Phonetic Dictionaries**: [AI4Bharat Indic-TTS](https://github.com/AI4Bharat/Indic-TTS) by **AI4Bharat (IIT Madras)**. License: **MIT License**. | |
| - **eSpeak-NG**: [eSpeak-NG](https://github.com/espeak-ng/espeak-ng) multi-lingual speech synthesizer. License: **GPL-3.0**. | |