| --- |
| license: cc-by-4.0 |
| dataset_info: |
| features: |
| - name: segment_id |
| dtype: string |
| - name: audio |
| dtype: |
| audio: |
| decode: false |
| - name: duration_seconds |
| dtype: int64 |
| - name: segment_text |
| dtype: string |
| - name: cs_terms_list |
| dtype: string |
| - name: cs_terms_count |
| dtype: int64 |
| - name: topic |
| dtype: string |
| - name: original_video_link |
| dtype: string |
| - name: original_video_title |
| dtype: string |
| - name: start_time |
| dtype: string |
| - name: end_time |
| dtype: string |
| splits: |
| - name: train |
| num_bytes: 14582022075 |
| num_examples: 11832 |
| - name: validation |
| num_bytes: 2139515036 |
| num_examples: 1714 |
| - name: test |
| num_bytes: 2026901460 |
| num_examples: 1614 |
| - name: hard |
| num_bytes: 814798996 |
| num_examples: 658 |
| download_size: 18312886260 |
| dataset_size: 19563237567 |
| configs: |
| - config_name: default |
| data_files: |
| - split: train |
| path: data/train-* |
| - split: validation |
| path: data/validation-* |
| - split: test |
| path: data/test-* |
| - split: hard |
| path: data/hard-* |
| task_categories: |
| - automatic-speech-recognition |
| language: |
| - vi |
| tags: |
| - medical |
| - code-switching |
| --- |
| # 🩺 ViMedCSS: A Vietnamese Medical Code-Switching Speech Dataset (LREC 2026) |
|
|
| ## 📖 Overview |
| ViMedCSS is a Vietnamese medical speech dataset for code-switching ASR, where each utterance contains at least one non-Vietnamese (mainly English) medical term embedded in Vietnamese speech. |
|
|
| ## 📊 Dataset Statistics |
| ### Split Statistics (from `ViMedCSS-Metadata`) |
| | Split | # Rows | Duration (hours) | Avg duration (s) | Total CS terms | |
| |---|---:|---:|---:|---:| |
| | train | 11,832 | 24.30 | 7.39 | 12,314 | |
| | validation | 1,714 | 3.57 | 7.49 | 1,814 | |
| | test | 1,614 | 3.39 | 7.56 | 1,695 | |
| | hard | 658 | 1.38 | 7.57 | 758 | |
| | **Total** | **15,818** | **32.64** | **7.43** | **16,581** | |
|
|
| ### Topic Statistics (from `ViMedCSS-Metadata`) |
| | Topic | # Rows | Duration (hours) | Total CS terms | |
| |---|---:|---:|---:| |
| | Medical Sciences | 6,836 | 14.68 | 7,459 | |
| | Pathology & Pathogens | 4,827 | 10.00 | 4,951 | |
| | Treatments | 1,969 | 3.80 | 1,985 | |
| | Nutrition | 1,155 | 2.14 | 1,155 | |
| | Diagnostics | 1,031 | 2.02 | 1,031 | |
|
|
| ## 🧾 Data Fields |
| Each row in metadata corresponds to one segment audio file, where: |
| - `segment_id` maps to `segment_id.wav` (for example: `Med_CS-100-17` -> `Med_CS-100-17.wav`) |
|
|
| Main fields: |
| - `segment_id`: utterance identifier |
| - `duration_seconds`: utterance duration |
| - `segment_text`: Vietnamese transcript containing code-switched term(s) |
| - `cs_terms_list`: semicolon-separated code-switched terms |
| - `cs_terms_count`: number of code-switched terms in the utterance |
| - `topic` (or `Topic` in one CSV): medical topic label |
| - `original_video_link`: source video URL |
| - `original_video_title`: source video title |
| - `start_time`, `end_time`: segment boundaries in source audio/video |
|
|
| When loaded from Hugging Face, an `audio` column is available with waveform bytes/path in the standard 🤗 Datasets `Audio` format. |
|
|
| ## 🔽 How to Load |
| Load directly with 🤗 Datasets: |
|
|
| ```python |
| from datasets import load_dataset |
| |
| dataset = load_dataset("tensorxt/ViMedCSS") |
| print(dataset) |
| ``` |
|
|
| Clone with Git LFS: |
|
|
| ```bash |
| git lfs install |
| git clone https://huggingface.co/datasets/tensorxt/ViMedCSS |
| ``` |
|
|
| ## 📝 Notes |
| - The paper reports the full corpus statistics (34.57h). |
| - The `hard` split is intended for evaluating rare/unseen code-switched medical terms, following the paper’s benchmark setup. |
|
|
| ## 📜 License |
| The paper states that data are collected from publicly available YouTube content for research purposes, and the medical dictionary resource used in construction is under institutional intellectual property licensing. |
|
|
| Please verify usage rights for your setting before redistribution or commercial use. |
|
|
| ## 🙏 Citation |
| If you use ViMedCSS, please cite the paper: https://arxiv.org/abs/2602.12911 |
|
|
| ```bibtex |
| @inproceedings{nguyen-etal-2026-vimedcss, |
| title = "{V}i{M}ed{CSS}: A Vietnamese Medical Code-Switching Speech Dataset \& Benchmark", |
| author = "Tung X. Nguyen, Nhu Vo, Giang-Son Nguyen, Duy Mai Hoang, Chien Dinh Huynh, Inigo Jauregi Unanue, Massimo Piccardi, Wray Buntine, Dung D. Le", |
| booktitle = "Proceedings of the 2026 Language Resources and Evaluation Conference (LREC 2026)", |
| year = "2026", |
| } |
| ``` |
