Model Card for Lite-Whisper large-v3-turbo
Lite-Whisper is a compressed version of OpenAI Whisper with LiteASR. See our GitHub repository and paper for details.
Benchmark Results
Following is the average word error rate (WER) evaluated on the ESB datasets:
| Model | Average WER (↓) | Encoder Size | Decoder Size |
|---|---|---|---|
| whisper-large-v3 | 10.1 | 635M | 907M |
| lite-whisper-large-v3-acc | 10.1 | 429M | 907M |
| lite-whisper-large-v3 | 10.2 | 377M | 907M |
| lite-whisper-large-v3-fast | 11.3 | 308M | 907M |
| whisper-large-v3-turbo | 10.1 | 635M | 172M |
| lite-whisper-large-v3-turbo-acc | 10.2 | 421M | 172M |
| lite-whisper-large-v3-turbo | 12.6 | 374M | 172M |
| lite-whisper-large-v3-turbo-fast | 20.1 | 313M | 172M |
| whisper-medium | 14.8 | 306M | 457M |
Citation
If you use LiteASR in your research, please cite the following paper:
@misc{kamahori2025liteasrefficientautomaticspeech,
title={LiteASR: Efficient Automatic Speech Recognition with Low-Rank Approximation},
author={Keisuke Kamahori and Jungo Kasai and Noriyuki Kojima and Baris Kasikci},
year={2025},
eprint={2502.20583},
archivePrefix={arXiv},
primaryClass={cs.LG},
url={https://arxiv.org/abs/2502.20583},
}