You can deploy this model and start earning money today!

Bindkushal/
IndicVoice-82M

Name: IndicVoice-82M
Availability: InStock

Views

No views yet

IndicVoice

A decoder-only neural TTS model for Indian languages, built on the Kokoro-82M architecture with a native Indic G2P frontend.

Author: Kushal Kant Bind — Chandigarh University Project: GSoC 2026, Sugar Labs GitHub: Bindkushal/indic-voice

Quick Start

bash

pip install git+https://github.com/Bindkushal/indic-g2p.git
pip install git+https://github.com/Bindkushal/indic-voice.git
apt-get install espeak-ng

python

from indicvoice import IndicPipeline
pipeline = IndicPipeline(lang_code="hi", repo_id="Bindkushal/IndicVoice-82M")
for gs, ps, audio in pipeline("नमस्ते दुनिया", voice="af_heart"):
    import soundfile as sf
    sf.write("output.wav", audio, 24000)

Files in This Repo

File	Description
`config.json`	Model architecture config
`indicvoice-v1_0.pth`	Model weights (82M params)
`voices/af_heart.pt`	Default voice style tensor
`voices/af_bella.pt`	Voice style tensor
`voices/am_adam.pt`	Voice style tensor

Supported Languages

Language	Code	Script	Status
Hindi	`hi`	Devanagari	Ready
Punjabi	`pa`	Gurmukhi	Ready
Bengali	`bn`	Bengali	Beta
English	`en`	Roman	Ready

Architecture

Base: Kokoro-82M (StyleTTS2 + ISTFTNet), Apache 2.0
G2P: indic-g2p — native Indic phonemizer
Fallback: espeak-ng for OOV words
Parameters: 82M
Sample rate: 24000 Hz

Citation

bibtex

@misc{bind2026indicvoice,
  title={IndicVoice: Decoder-Only Neural TTS with Native G2P for Indian Languages},
  author={Kushal Kant Bind},
  year={2026},
  institution={Chandigarh University},
  note={GSoC 2026, Sugar Labs}
}

Acknowledgements

hexgrad/kokoro — base TTS architecture (Apache 2.0)
AI4Bharat — IndicVoices-R dataset
IIT Madras — IndicTTS dataset

License

Apache 2.0