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2023310197mehak/indic-tts-v1
indic-tts-v1 is a machine learning model from 2023310197mehak. Use it for the machine learning task on the model card, and read the license before you ship it in a product.
Indic-TTS-v1 is a multilingual Text-to-Speech (TTS) model trained on dataset covering 11 major Indic languages. Built upon the Qwen3-TTS architecture, it generates natural-sounding speech from input text across variou…
Downloads · 30 days
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From the Hugging Face model README
Indic-TTS-v1 is a multilingual Text-to-Speech (TTS) model trained on dataset covering 11 major Indic languages. Built upon the Qwen3-TTS architecture, it generates natural-sounding speech from input text across various South Asian languages and dialects.
The model has been trained on speech data from the following 11 Indic languages:
| Language | ISO Code | Language Family |
|---|---|---|
| Hindi | hi | Indo-Aryan |
| Bengali | bn | Indo-Aryan |
| Marathi | mr | Indo-Aryan |
| Telugu | te | Dravidian |
| Tamil | ta | Dravidian |
| Gujarati | gu | Indo-Aryan |
| Kannada | kn | Dravidian |
| Malayalam | ml | Dravidian |
| Odia | or | Indo-Aryan |
| Punjabi | pa | Indo-Aryan |
| Urdu | ur | Indo-Aryan |
Below is a basic example of how to load and use the model for audio synthesis:
import torch
# Example model loading (adjust import based on your specific implementation/pipeline)
# from transformers import AutoModelForTextToWaveform, AutoTokenizer
model_id = "2023310197mehak/indic-tts-v1"
# Load model & tokenizer
# tokenizer = AutoTokenizer.from_pretrained(model_id)
# model = AutoModelForTextToWaveform.from_pretrained(model_id)
# Synthesize speech
# text = "नमस्ते, आप कैसे हैं?" # Example Hindi text
# inputs = tokenizer(text, return_tensors="pt")
# with torch.no_grad():
# audio = model.generate(**inputs)