Whisper Large V3 Vaani Hindi

🚀 Whisper-large-v3-vaani-hindi

This is a fine-tuned version of OpenAI's Whisper-Large-V3, trained on approximately 718 hours of transcribed Hindi speech from multiple datasets.

🚀 Quick Start

This model can be used with the pipeline function from the Transformers module.

💻 Usage Examples

Basic Usage

import torch
from transformers import pipeline

audio = "path to the audio file to be transcribed"
device = "cuda:0" if torch.cuda.is_available() else "cpu"
modelTags="ARTPARK-IISc/whisper-large-v3-vaani-hindi"
transcribe = pipeline(task="automatic-speech-recognition", model=modelTags, chunk_length_s=30, device=device)
transcribe.model.config.forced_decoder_ids = transcribe.tokenizer.get_decoder_prompt_ids(language="hi", task="transcribe")

print('Transcription: ', transcribe(audio)["text"])

🔧 Technical Details

Training and Evaluation

The model has been fine-tuned using the following datasets:

• Vaani
• Gramvaani
• IndicVoices
• Fleurs
• IndicTTS
• Commonvoice

The performance of the model was evaluated using multiple datasets, and the evaluation results are provided below.

📄 License

This project is licensed under the Apache-2.0 license.