Automatic Speech Recognition
Transformers.js
PyTorch
ONNX
Vietnamese
whisper
audio
hf-asr-leaderboard
Instructions to use huuquyet/PhoWhisper-medium with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers.js
How to use huuquyet/PhoWhisper-medium with Transformers.js:
// npm i @huggingface/transformers import { pipeline } from '@huggingface/transformers'; // Allocate pipeline const pipe = await pipeline('automatic-speech-recognition', 'huuquyet/PhoWhisper-medium');
| license: wtfpl | |
| language: | |
| - vi | |
| library_name: transformers.js | |
| https://hf.co/vinai/PhoWhisper-medium with ONNX weights to be compatible with Transformers.js. | |
| Please check out this demo using this model: | |
| [](https://huggingface.co/spaces/huuquyet/PhoWhisper-next) | |
| # PhoWhisper: Automatic Speech Recognition for Vietnamese | |
| We introduce **PhoWhisper** in five versions for Vietnamese automatic speech recognition. PhoWhisper's robustness is achieved through fine-tuning the multilingual [Whisper](https://github.com/openai/whisper) on an 844-hour dataset that encompasses diverse Vietnamese accents. Our experimental study demonstrates state-of-the-art performances of PhoWhisper on benchmark Vietnamese ASR datasets. Please **cite** our PhoWhisper paper when it is used to help produce published results or is incorporated into other software: | |
| ``` | |
| @inproceedings{PhoWhisper, | |
| title = {{PhoWhisper: Automatic Speech Recognition for Vietnamese}}, | |
| author = {Thanh-Thien Le and Linh The Nguyen and Dat Quoc Nguyen}, | |
| booktitle = {Proceedings of the ICLR 2024 Tiny Papers track}, | |
| year = {2024} | |
| } | |
| ``` | |
| For further information or requests, please go to [PhoWhisper's homepage](https://github.com/VinAIResearch/PhoWhisper)! |