efficient-speech/lite-whisper-large-v3-turbo

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}, 
}