--- language: - vi - en - de - fr - zh license: mit task_categories: - automatic-speech-recognition viewer: true dataset_info: - config_name: Chinese features: - name: audio dtype: audio: sampling_rate: 16000 - name: text dtype: string - name: duration dtype: float64 splits: - name: train num_bytes: 182566135.142 num_examples: 1242 - name: eval num_bytes: 12333509 num_examples: 91 - name: test num_bytes: 33014034 num_examples: 225 download_size: 227567289 dataset_size: 227913678.142 - config_name: English features: - name: audio dtype: audio: sampling_rate: 16000 - name: text dtype: string - name: duration dtype: float64 splits: - name: train num_bytes: 2789314997.152 num_examples: 25512 - name: eval num_bytes: 299242087.632 num_examples: 2816 - name: test num_bytes: 553873172.749 num_examples: 4751 download_size: 3627859275 dataset_size: 3642430257.533 - config_name: French features: - name: audio dtype: audio: sampling_rate: 16000 - name: text dtype: string - name: duration dtype: float64 splits: - name: train num_bytes: 168642145.231 num_examples: 1403 - name: eval num_bytes: 5164908 num_examples: 42 - name: test num_bytes: 42780388 num_examples: 344 download_size: 216118671 dataset_size: 216587441.231 - config_name: German features: - name: audio dtype: audio - name: text dtype: string - name: duration dtype: float64 splits: - name: train num_bytes: 181312217.029 num_examples: 1443 - name: test num_bytes: 137762006.256 num_examples: 1091 - name: eval num_bytes: 35475098 num_examples: 287 download_size: 354494147 dataset_size: 354549321.285 - config_name: Vietnamese features: - name: audio dtype: audio - name: text dtype: string - name: duration dtype: float64 splits: - name: train num_bytes: 56584901.453 num_examples: 2773 - name: test num_bytes: 69598082.31 num_examples: 3437 - name: dev num_bytes: 57617298.896 num_examples: 2912 download_size: 181789393 dataset_size: 183800282.659 configs: - config_name: Chinese data_files: - split: train path: Chinese/train-* - split: eval path: Chinese/eval-* - split: test path: Chinese/test-* - config_name: English data_files: - split: train path: English/train-* - split: eval path: English/eval-* - split: test path: English/test-* - config_name: French data_files: - split: train path: French/train-* - split: eval path: French/eval-* - split: test path: French/test-* - config_name: German data_files: - split: train path: German/train-* - split: test path: German/test-* - split: eval path: German/eval-* - config_name: Vietnamese data_files: - split: train path: Vietnamese/train-* - split: test path: Vietnamese/test-* - split: dev path: Vietnamese/dev-* tags: - medical --- # MultiMed: Multilingual Medical Speech Recognition via Attention Encoder Decoder **
ACL 2025
**
Khai Le-Duc, Phuc Phan, Tan-Hanh Pham, Bach Phan Tat,
Minh-Huong Ngo, Chris Ngo, Thanh Nguyen-Tang, Truong-Son Hy
> Please press ⭐ button and/or cite papers if you feel helpful.

* **Abstract:** Multilingual automatic speech recognition (ASR) in the medical domain serves as a foundational task for various downstream applications such as speech translation, spoken language understanding, and voice-activated assistants. This technology improves patient care by enabling efficient communication across language barriers, alleviating specialized workforce shortages, and facilitating improved diagnosis and treatment, particularly during pandemics. In this work, we introduce MultiMed, the first multilingual medical ASR dataset, along with the first collection of small-to-large end-to-end medical ASR models, spanning five languages: Vietnamese, English, German, French, and Mandarin Chinese. To our best knowledge, MultiMed stands as **the world’s largest medical ASR dataset across all major benchmarks**: total duration, number of recording conditions, number of accents, and number of speaking roles. Furthermore, we present the first multilinguality study for medical ASR, which includes reproducible empirical baselines, a monolinguality-multilinguality analysis, Attention Encoder Decoder (AED) vs Hybrid comparative study and a linguistic analysis. We present practical ASR end-to-end training schemes optimized for a fixed number of trainable parameters that are common in industry settings. All code, data, and models are available online: [https://github.com/leduckhai/MultiMed/tree/master/MultiMed](https://github.com/leduckhai/MultiMed/tree/master/MultiMed). * **Citation:** Please cite this paper: [https://arxiv.org/abs/2409.14074](https://arxiv.org/abs/2409.14074) ``` bibtex @article{le2024multimed, title={MultiMed: Multilingual Medical Speech Recognition via Attention Encoder Decoder}, author={Le-Duc, Khai and Phan, Phuc and Pham, Tan-Hanh and Tat, Bach Phan and Ngo, Minh-Huong and Ngo, Chris and Nguyen-Tang, Thanh and Hy, Truong-Son}, journal={arXiv preprint arXiv:2409.14074}, year={2024} } ``` ## Dataset and Pre-trained Models: Dataset: [🤗 HuggingFace dataset](https://huggingface.co/datasets/leduckhai/MultiMed), [Paperswithcodes dataset](https://paperswithcode.com/dataset/multimed) Pre-trained models: [🤗 HuggingFace models](https://huggingface.co/leduckhai/MultiMed) | Model Name | Description | Link | |------------------|--------------------------------------------|----------------------------------------------------------------------| | `Whisper-Small-Chinese` | Small model fine-tuned on medical Chinese set | [Hugging Face models](https://huggingface.co/leduckhai/MultiMed-ST/tree/main/asr/whisper-small-chinese) | | `Whisper-Small-English` | Small model fine-tuned on medical English set | [Hugging Face models](https://huggingface.co/leduckhai/MultiMed-ST/tree/main/asr/whisper-small-english) | | `Whisper-Small-French` | Small model fine-tuned on medical French set | [Hugging Face models](https://huggingface.co/leduckhai/MultiMed-ST/tree/main/asr/whisper-small-french) | | `Whisper-Small-German` | Small model fine-tuned on medical German set | [Hugging Face models](https://huggingface.co/leduckhai/MultiMed-ST/tree/main/asr/whisper-small-german) | | `Whisper-Small-Vietnamese` | Small model fine-tuned on medical Vietnamese set | [Hugging Face models](https://huggingface.co/leduckhai/MultiMed-ST/tree/main/asr/whisper-small-vietnamese) | | `Whisper-Small-Multilingual` | Small model fine-tuned on medical Multilingual set (5 languages) | [Hugging Face models](https://huggingface.co/leduckhai/MultiMed-ST/tree/main/asr/whisper-small-multilingual) | ## Contact: If any links are broken, please contact me for fixing! Thanks [Phan Phuc](https://www.linkedin.com/in/pphuc/) for dataset viewer <3 ``` Le Duc Khai University of Toronto, Canada Email: duckhai.le@mail.utoronto.ca GitHub: https://github.com/leduckhai ```