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π©Ί ViMedCSS: A Vietnamese Medical Code-Switching Speech Dataset (LREC 2026)
π 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.
π 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 |
π§Ύ Data Fields
Each row in metadata corresponds to one segment audio file, where:
segment_idmaps tosegment_id.wav(for example:Med_CS-100-17->Med_CS-100-17.wav)
Main fields:
segment_id: utterance identifierduration_seconds: utterance durationsegment_text: Vietnamese transcript containing code-switched term(s)cs_terms_list: semicolon-separated code-switched termscs_terms_count: number of code-switched terms in the utterancetopic(orTopicin one CSV): medical topic labeloriginal_video_link: source video URLoriginal_video_title: source video titlestart_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 π€ Datasets Audio format.
π½ How to Load
Load directly with π€ Datasets:
from datasets import load_dataset
dataset = load_dataset("tensorxt/ViMedCSS")
print(dataset)
Clone with Git LFS:
git lfs install
git clone https://huggingface.co/datasets/tensorxt/ViMedCSS
π Notes
- The paper reports the full corpus statistics (34.57h).
- The
hardsplit is intended for evaluating rare/unseen code-switched medical terms, following the paperβs benchmark setup.
π 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.
π Citation
If you use ViMedCSS, please cite the paper: https://arxiv.org/abs/2602.12911
@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",
}
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