|
--- |
|
base_model: openai/whisper-medium |
|
library_name: transformers |
|
license: apache-2.0 |
|
pipeline_tag: automatic-speech-recognition |
|
tags: |
|
- audio |
|
- automatic-speech-recognition |
|
- whisper |
|
- hf-asr-leaderboard |
|
--- |
|
|
|
<!-- Provide a quick summary of what the model is/does. --> |
|
|
|
Lite-Whisper is a compressed version of OpenAI Whisper with LiteASR. See our [GitHub repository](https://github.com/efeslab/LiteASR) and [paper](https://arxiv.org/abs/2502.20583) for details. |
|
|
|
## Benchmark Results |
|
|
|
Following is the average word error rate (WER) evaluated on the [ESB datasets](https://huggingface.co/datasets/hf-audio/esb-datasets-test-only-sorted): |
|
|
|
| Model | Average WER (↓) | Encoder Size | Decoder Size | |
|
|-------|----------------|--------------|--------------| |
|
| [whisper-tiny](https://huggingface.co/openai/whisper-tiny) | 22.01 | 7.63M | 29.55M | |
|
| [lite-whisper-tiny-acc](https://huggingface.co/efficient-speech/lite-whisper-tiny-acc) | 22.97 | 7.41M | 29.55M | |
|
| [lite-whisper-tiny](https://huggingface.co/efficient-speech/lite-whisper-tiny) | 23.95 | 7.00M | 29.55M | |
|
| [lite-whisper-tiny-fast](https://huggingface.co/efficient-speech/lite-whisper-tiny-fast) | 27.09 | 6.48M | 29.55M | |
|
| | | | | |
|
| [whisper-base](https://huggingface.co/openai/whisper-base) | 17.67 | 19.82M | 52.00M | |
|
| [lite-whisper-base-acc](https://huggingface.co/efficient-speech/lite-whisper-base-acc) | 19.07 | 18.64M | 52.00M | |
|
| [lite-whisper-base](https://huggingface.co/efficient-speech/lite-whisper-base) | 19.71 | 17.44M | 52.00M | |
|
| [lite-whisper-base-fast](https://huggingface.co/efficient-speech/lite-whisper-base-fast) | 23.05 | 16.07M | 52.00M | |
|
| | | | | |
|
| [whisper-small](https://huggingface.co/openai/whisper-small) | 15.89 | 87.00M | 153.58M | |
|
| [lite-whisper-small-acc](https://huggingface.co/efficient-speech/lite-whisper-small-acc) | 15.37 | 76.99M | 153.58M | |
|
| [lite-whisper-small](https://huggingface.co/efficient-speech/lite-whisper-small) | 14.96 | 70.16M | 153.58M | |
|
| [lite-whisper-small-fast](https://huggingface.co/efficient-speech/lite-whisper-small-fast) | 14.92 | 63.11M | 153.58M | |
|
| | | | | |
|
| [whisper-medium](https://huggingface.co/openai/whisper-medium) | 15.12 | 305.68M | 456.64M | |
|
| [lite-whisper-medium-acc](https://huggingface.co/efficient-speech/lite-whisper-medium-acc) | 13.46 | 269.93M | 456.64M | |
|
| [lite-whisper-medium](https://huggingface.co/efficient-speech/lite-whisper-medium) | 14.50 | 239.99M | 456.64M | |
|
| [lite-whisper-medium-fast](https://huggingface.co/efficient-speech/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}, |
|
} |
|
``` |
