pip install whisperplusYou can find the models on the HuggingFace Spaces or on the HuggingFace Model Hub
To use the whisperplus library, follow the steps below for different tasks:
from whisperplus import SpeechToTextPipeline, download_and_convert_to_mp3
url = "https://www.youtube.com/watch?v=di3rHkEZuUw"
video_path = download_and_convert_to_mp3(url)
pipeline = SpeechToTextPipeline(model_id="openai/whisper-large-v3")
transcript = pipeline(
audio_path=video_path, model_id="openai/whisper-large-v3", language="english
)
return transcript### Contributing
pip install -r dev-requirements.txt
pre-commit install
pre-commit run --all-filesThis project is licensed under the terms of the Apache License 2.0.
This project is based on the HuggingFace Transformers library.
@misc{radford2022whisper,
doi = {10.48550/ARXIV.2212.04356},
url = {https://arxiv.org/abs/2212.04356},
author = {Radford, Alec and Kim, Jong Wook and Xu, Tao and Brockman, Greg and McLeavey, Christine and Sutskever, Ilya},
title = {Robust Speech Recognition via Large-Scale Weak Supervision},
publisher = {arXiv},
year = {2022},
copyright = {arXiv.org perpetual, non-exclusive license}
}