VITS TTS for Indian Languages
This repository contains a VITS-based Text-to-Speech (TTS) model fine-tuned for Indian languages. The model supports multiple Indian languages and a wide range of speaking styles and emotions, making it suitable for diverse use cases such as conversational AI, audiobooks, and more.
Model Overview
The model ai4bharat/vits_rasa_13 is based on the VITS architecture and supports the following features:
- Languages: Multiple Indian languages.
- Styles: Various speaking styles and emotions.
- Speaker IDs: Predefined speaker profiles for male and female voices.
Installation
pip install transformers torch
Usage
Here's a quick example to get started:
import soundfile as sf
from transformers import AutoModel, AutoTokenizer
model = AutoModel.from_pretrained("ai4bharat/vits_rasa_13", trust_remote_code=True).to("cuda")
tokenizer = AutoTokenizer.from_pretrained("ai4bharat/vits_rasa_13", trust_remote_code=True)
text = "ਕੀ ਮੈਂ ਇਸ ਹਫਤੇ ਦੇ ਅੰਤ ਵਿੱਚ ਰੁੱਝਿਆ ਹੋਇਆ ਹਾਂ?" # Example text in Punjabi
speaker_id = 16 # PAN_M
style_id = 0 # ALEXA
inputs = tokenizer(text=text, return_tensors="pt").to("cuda")
outputs = model(inputs['input_ids'], speaker_id=speaker_id, emotion_id=style_id)
sf.write("audio.wav", outputs.waveform.squeeze(), model.config.sampling_rate)
print(outputs.waveform.shape)
Supported Languages
AssameseBengaliBodoDogriKannadaMaithiliMalayalamMarathiNepaliPunjabiSanskritTamilTelugu
Speaker-Style Identifier Overview
| Speaker Name | Speaker ID |
|---|---|
| ASM_F | 0 |
| ASM_M | 1 |
| BEN_F | 2 |
| BEN_M | 3 |
| BRX_F | 4 |
| BRX_M | 5 |
| DOI_F | 6 |
| DOI_M | 7 |
| KAN_F | 8 |
| KAN_M | 9 |
| MAI_M | 10 |
| MAL_F | 11 |
| MAR_F | 12 |
| MAR_M | 13 |
| NEP_F | 14 |
| PAN_F | 15 |
| PAN_M | 16 |
| SAN_M | 17 |
| TAM_F | 18 |
| TEL_F | 19 |
| Style Name | Style ID |
|---|---|
| ALEXA | 0 |
| ANGER | 1 |
| BB | 2 |
| BOOK | 3 |
| CONV | 4 |
| DIGI | 5 |
| DISGUST | 6 |
| FEAR | 7 |
| HAPPY | 8 |
| NEWS | 10 |
| SAD | 12 |
| SURPRISE | 14 |
| UMANG | 15 |
| WIKI | 16 |
Citation
If you use this model in your research, please cite:
@article{ai4bharat_vits_rasa_13,
title={VITS TTS for Indian Languages},
author={Ashwin Sankar},
year={2024},
publisher={Hugging Face}
}
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