metadata
base_model: openai/whisper-small
library_name: transformers
license: apache-2.0
pipeline_tag: automatic-speech-recognition
tags:
- audio
- automatic-speech-recognition
- whisper
- hf-asr-leaderboard
Lite-Whisper is a compressed version of OpenAI Whisper with LiteASR. See our GitHub repository and paper for details.
This model revised the name of “efficient-speech/lite-whisper-small-fast” and merged any missing files to facilitate subsequent conversion to ONNX format or for other purposes.
Benchmark Results
Following is the average word error rate (WER) evaluated on the ESB datasets:
| Model | Average WER (↓) | Encoder Size | Decoder Size |
|---|---|---|---|
| whisper-tiny | 22.01 | 7.63M | 29.55M |
| lite-whisper-tiny-acc | 22.97 | 7.41M | 29.55M |
| lite-whisper-tiny | 23.95 | 7.00M | 29.55M |
| lite-whisper-tiny-fast | 27.09 | 6.48M | 29.55M |
| whisper-base | 17.67 | 19.82M | 52.00M |
| lite-whisper-base-acc | 19.07 | 18.64M | 52.00M |
| lite-whisper-base | 19.71 | 17.44M | 52.00M |
| lite-whisper-base-fast | 23.05 | 16.07M | 52.00M |
| whisper-small | 15.89 | 87.00M | 153.58M |
| lite-whisper-small-acc | 15.37 | 76.99M | 153.58M |
| lite-whisper-small | 14.96 | 70.16M | 153.58M |
| lite-whisper-small-fast | 14.92 | 63.11M | 153.58M |
| whisper-medium | 15.12 | 305.68M | 456.64M |
| lite-whisper-medium-acc | 13.46 | 269.93M | 456.64M |
| lite-whisper-medium | 14.50 | 239.99M | 456.64M |
| lite-whisper-medium-fast | 14.52 | 215.31M | 456.64M |
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},
}