Datasets:

leduckhai
/

MultiMed-ST

@@ -224,156 +224,58 @@ language:
 - zh
 - fr
 ---
-# Dataset Card for Dataset Name
-<!-- Provide a quick summary of the dataset. -->
-This dataset is an extended version of [leduckhai/MultiMed](https://huggingface.co/datasets/leduckhai/MultiMed).
-This dataset is still in the development stage!
-## Dataset Details
-### Dataset Description
-<!-- Provide a longer summary of what this dataset is. -->
-<!-- - **Curated by:** [More Information Needed]
-- **Funded by [optional]:** [More Information Needed]
-- **Shared by [optional]:** [More Information Needed] -->
-- **Languages (NLP):** Vietnamese (vn), English (en), Traditional Chinese (zh_TW), Simplified Chinese (zh_CN), German (de), French (fr)
-<!-- - **License:** [More Information Needed] -->
-### Dataset Sources
-<!-- Provide the basic links for the dataset. -->
-- **Repository:** [leduckhai/MultiMed](https://huggingface.co/datasets/leduckhai/MultiMed)
-<!-- - **Paper [optional]:** [More Information Needed]
-- **Demo [optional]:** [More Information Needed] -->
-<!-- ## Uses -->
-<!-- Address questions around how the dataset is intended to be used. -->
-<!-- ### Direct Use -->
-<!-- This section describes suitable use cases for the dataset. -->
-<!-- [More Information Needed] -->
-<!-- ### Out-of-Scope Use -->
-<!-- This section addresses misuse, malicious use, and uses that the dataset will not work well for. -->
-<!-- [More Information Needed] -->
-<!-- ## Dataset Structure -->
-<!-- This section provides a description of the dataset fields, and additional information about the dataset structure such as criteria used to create the splits, relationships between data points, etc. -->
-<!-- [More Information Needed] -->
-## Dataset Creation
-<!-- ### Curation Rationale -->
-<!-- Motivation for the creation of this dataset. -->
-<!-- [More Information Needed] -->
-<!-- ### Source Data -->
-<!-- This section describes the source data (e.g. news text and headlines, social media posts, translated sentences, ...). -->
-<!-- #### Data Collection and Processing -->
-<!-- This section describes the data collection and processing process such as data selection criteria, filtering and normalization methods, tools and libraries used, etc. -->
-<!-- [More Information Needed] -->
-<!-- #### Who are the source data producers? -->
-<!-- This section describes the people or systems who originally created the data. It should also include self-reported demographic or identity information for the source data creators if this information is available. -->
-<!-- [More Information Needed] -->
-<!-- ### Annotations [optional] -->
-<!-- If the dataset contains annotations which are not part of the initial data collection, use this section to describe them. -->
-<!-- #### Annotation process -->
-<!-- This section describes the annotation process such as annotation tools used in the process, the amount of data annotated, annotation guidelines provided to the annotators, interannotator statistics, annotation validation, etc. -->
-<!-- [More Information Needed] -->
-#### Who are the developers?
-```bash
-Bui Nguyen Kim Hai (Eötvös Loránd University, Hungary) -- Main Developer
-Bach Phan Tat (KU Leuven, Belgium) -- Advisor
-Khai Le-Duc (University of Toronto, Canada) -- Advisor
 ```
-#### Who are the annotators?
-```bash
-Thanh-Thuy Nguyen (HCMC Open University, Vietnam)
-Ly Nguyen (IÉSEG School of Management, France)
-Tuan-Minh Phan (Technical University Dortmund, Germany)
-Phuong Tran (University of Hertfordshire, UK)
 ```
-<!-- This section describes the people or systems who created the annotations. -->
-<!-- [More Information Needed] -->
-<!-- #### Personal and Sensitive Information -->
-<!-- State whether the dataset contains data that might be considered personal, sensitive, or private (e.g., data that reveals addresses, uniquely identifiable names or aliases, racial or ethnic origins, sexual orientations, religious beliefs, political opinions, financial or health data, etc.). If efforts were made to anonymize the data, describe the anonymization process. -->
-<!-- [More Information Needed] -->
-<!-- ## Bias, Risks, and Limitations -->
-<!-- This section is meant to convey both technical and sociotechnical limitations. -->
-<!-- [More Information Needed] -->
-<!-- ### Recommendations -->
-<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
-<!-- Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations. -->
-<!-- ## Citation [optional] -->
-<!-- If there is a paper or blog post introducing the dataset, the APA and Bibtex information for that should go in this section. -->
-<!-- **BibTeX:** -->
-<!-- [More Information Needed] -->
-<!-- **APA:** -->
-<!-- [More Information Needed] -->
-<!-- ## Glossary [optional] -->
-<!-- If relevant, include terms and calculations in this section that can help readers understand the dataset or dataset card. -->
-<!-- [More Information Needed] -->
-<!-- ## More Information [optional] -->
-<!-- [More Information Needed] -->
-## Dataset Card Contact / Dataset Card Author
-```bash
-Bui Nguyen Kim Hai
 Eötvös Loránd University, Hungary
 Email: htlulem185@gmail.com
 ```

 - zh
 - fr
 ---
+# MultiMed-ST: Large-scale Many-to-many Multilingual Medical Speech Translation
+**<div align="center">Preprint</div>**
+<div align="center">Khai Le-Duc*, Tuyen Tran*,</div>
+<div align="center">Bach Phan Tat, Nguyen Kim Hai Bui, Quan Dang, Hung-Phong Tran, Thanh-Thuy Nguyen, Ly Nguyen, Tuan-Minh Phan, Thi Thu Phuong Tran, Chris Ngo,</div>
+<div align="center">Nguyen X. Khanh**, Thanh Nguyen-Tang**</div>
+<div align="center">*Equal contribution</div>
+<div align="center">**Equal supervision</div>
+* **Abstract:**
+Multilingual speech translation (ST) in the medical domain  enhances 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 present the first systematic study on medical ST, to our best knowledge, by releasing *MultiMed-ST*, a large-scale ST dataset for the medical domain, spanning all translation directions in five languages: Vietnamese, English, German, French,  Traditional Chinese and Simplified Chinese, together with the models. With 290,000 samples, our dataset is the largest medical machine translation (MT) dataset and the largest many-to-many multilingual ST among all domains. Secondly, we present the most extensive analysis study in ST research to date, including: empirical baselines, bilingual-multilingual comparative study, end-to-end vs. cascaded comparative study, task-specific vs. multi-task sequence-to-sequence (seq2seq) comparative study, code-switch analysis, and quantitative-qualitative error analysis. All code, data, and models are available online:  [https://github.com/leduckhai/MultiMed-ST](https://github.com/leduckhai/MultiMed-ST).
+* **Citation:**
+Please cite this paper: [https://arxiv.org/abs/2504.03546](https://arxiv.org/abs/2504.03546)
+``` bibtex
+@article{le2025multimedst,
+  title={MultiMed-ST: Large-scale Many-to-many Multilingual Medical Speech Translation},
+  author={Le-Duc, Khai and Tran, Tuyen and Tat, Bach Phan and Bui, Nguyen Kim Hai and Dang, Quan and Tran, Hung-Phong and Nguyen, Thanh-Thuy and Nguyen, Ly and Phan, Tuan-Minh and Tran, Thi Thu Phuong and others},
+  journal={arXiv preprint arXiv:2504.03546},
+  year={2025}
+}
+```
+## Dataset and Models:
+Dataset: [HuggingFace dataset](https://huggingface.co/datasets/leduckhai/MultiMed-ST)
+Fine-tuned models: [HuggingFace models](https://huggingface.co/leduckhai/MultiMed-ST)
+## Contact:
+Core developers:
+**Khai Le-Duc**
 ```
+University of Toronto, Canada
+Email: duckhai.le@mail.utoronto.ca
+GitHub: https://github.com/leduckhai
 ```
+**Tuyen Tran**
+```
+Hanoi University of Science and Technology, Vietnam
+Email: tuyencbt@gmail.com
+```
+**Bui Nguyen Kim Hai**
+```
 Eötvös Loránd University, Hungary
 Email: htlulem185@gmail.com
 ```