Datasets:

tensorxt
/

ViMedCSS

@@ -1,162 +1,97 @@
 ---
-license: cc-by-4.0
-dataset_info:
-  features:
-  - name: audio
-    dtype: audio
-  splits:
-  - name: train
-    num_bytes: 20465198175
-    num_examples: 15814
-  download_size: 18305122770
-  dataset_size: 20465198175
-configs:
-- config_name: default
-  data_files:
-  - split: train
-    path: data/train-*
-task_categories:
-- automatic-speech-recognition
-language:
-- vi
-tags:
-- medical
-- code-switching
 ---
-# Dataset Card for Dataset Name
-<!-- Provide a quick summary of the dataset. -->
-This dataset card aims to be a base template for new datasets. It has been generated using [this raw template](https://github.com/huggingface/huggingface_hub/blob/main/src/huggingface_hub/templates/datasetcard_template.md?plain=1).
-## Dataset Details
-### Dataset Description
-<!-- Provide a longer summary of what this dataset is. -->
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-### Dataset Sources [optional]
-<!-- Provide the basic links for the dataset. -->
-- **Repository:** [More Information Needed]
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-## Uses
-<!-- Address questions around how the dataset is intended to be used. -->
-### Direct Use
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-### Out-of-Scope Use
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-## Dataset Structure
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-## Dataset Creation
-### Curation Rationale
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-### Source Data
-<!-- This section describes the source data (e.g. news text and headlines, social media posts, translated sentences, ...). -->
-#### Data Collection and Processing
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-#### Who are the source data producers?
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-#### Personal and Sensitive Information
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 ---
+license: other
 ---
+# 🩺 ViMedCSS: Vietnamese Medical Code-Switching Speech Dataset
+## 📖 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.
+This dataset card is prepared from:
+- The metadata files in `ViMedCSS-Metadata` (`train_set.csv`, `valid_set.csv`, `test_set.csv`, `hard_set.csv`)
+- The paper: `Improving_Code_Switching_Detection_of_ASR_Models_for_Medical_Vietnamese_Speech (1).pdf`
+From the paper, the full ViMedCSS corpus is reported as:
+- 34.57 hours
+- 16,576 utterances
+- 5 medical topics
+- 4 splits including a dedicated `hard` split for rare/unseen terms
+From the provided CSV metadata in this release, the indexed subset contains:
+- 15,818 rows
+- 15,814 unique `segment_id`
+- 32.64 hours total duration
+- 16,581 total code-switched term occurrences
+- 889 distinct code-switched medical terms
+## 📊 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, 16,576 utterances).
+- The CSV metadata bundled here describes a smaller processed subset (32.64h, 15,818 rows).
+- 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:
+```bibtex
+@misc{nguyen_vimedcss,
+  title={ViMedCSS: A Vietnamese Medical Code-Switching Speech Dataset \& Benchmark},
+  author={Nguyen, Tung X. and Vo, Nhu and Nguyen, Giang-Son and Hoang, Duy Mai and Huynh, Chien Dinh and Jauregi Unanue, Inigo and Piccardi, Massimo and Buntine, Wray and Le, Dung D.},
+}
+```