metadata

license: apache-2.0
datasets:
  - ARTPARK-IISc/Vaani
language:
  - hi
base_model:
  - openai/whisper-small
pipeline_tag: automatic-speech-recognition

Whisper-small-vaani-kannada

This is a fine-tuned version of OpenAI's Whisper-Small, trained on Kannada speech from multiple datasets.

Usage

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


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-small-vaani-kannada"
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="ka", task="transcribe")

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

Training and Evaluation

The models has finetuned using folllowing dataset Vaani , Fleurs,IndicTTS

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

Dataset	WER
Fleurs	29.16
IndicTTS	15.27
Kathbath	33.94
Kathbath Noisy	38.46
Vaani	69.78