metadata
license: cc-by-4.0
language:
- as
- bn
- brx
- doi
- kn
- mai
- ml
- mr
- ne
- pa
- sa
- ta
- te
library_name: transformers
pipeline_tag: text-to-speech
tags:
- text-to-speech
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 | Style Name | Style ID |
|---|---|---|---|
| ASM_F | 0 | ALEXA | 0 |
| ASM_M | 1 | ANGER | 1 |
| BEN_F | 2 | BB | 2 |
| BEN_M | 3 | BOOK | 3 |
| BRX_F | 4 | CONV | 4 |
| BRX_M | 5 | DIGI | 5 |
| DOI_F | 6 | DISGUST | 6 |
| DOI_M | 7 | FEAR | 7 |
| KAN_F | 8 | HAPPY | 8 |
| KAN_M | 9 | NEWS | 10 |
| MAI_M | 10 | SAD | 12 |
| MAL_F | 11 | SURPRISE | 14 |
| MAR_F | 12 | UMANG | 15 |
| MAR_M | 13 | WIKI | 16 |
| NEP_F | 14 | ||
| PAN_F | 15 | ||
| PAN_M | 16 | ||
| SAN_M | 17 | ||
| TAM_F | 18 | ||
| TEL_F | 19 |
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}
}