efficient-speech
/

lite-whisper-medium-fast

@@ -1,199 +1,58 @@
 ---
 library_name: transformers
-tags: []
 ---
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 ---
+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 |
+| &nbsp; | &nbsp; | &nbsp; | &nbsp; |
+| [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 |
+| &nbsp; | &nbsp; | &nbsp; | &nbsp; |
+| [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 |
+| &nbsp; | &nbsp; | &nbsp; | &nbsp; |
+| [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},
+}
+```