README.md

---
language: en
license: mit
tags:
  - sign-language
  - mediapipe
  - vietnamese
  - keypoints
  - npz
size_categories:
  - 50GB+
task_categories:
  - other
custom_task: sign-language-recognition
pretty_name: VOYA Vietnamese Sign Language (VOYA_VSL)
---

# VOYA Vietnamese Sign Language (VOYA_VSL)

VOYA_VSL is a Vietnamese Sign Language dataset collected and preprocessed for research in **sign language recognition**.  
The dataset consists of sequences of keypoints extracted using MediaPipe, where each sequence represents a sign language video.

## 📦 Dataset Information

- **Format**: `.npz` (NumPy compressed)
- **Number of samples**: ~161
- **Sample structure**:
  - `sequences`: a matrix with shape `(60, 1605)` (60 frames, 1605 keypoints/features per frame)
  - `labels`: class index (int32)

## 📂 Dataset Structure

```
VOYA_VSL/
│── Merged/
│   ├── class_0001.npz
│   ├── class_0002.npz
│   ├── ...
│   └── class_0161.npz
│── labels.json
│── dataset.py
└── README.md
```

- `Merged/` : contains per-class data stored as `.npz` files  
- `labels.json` : maps `class_xxxx` → sign name  
- `dataset.py` : script to load dataset with Hugging Face Datasets  
- `README.md` : dataset description

## 🛠️ Usage
```python
from datasets import load_dataset

# Load the VOYA_VSL dataset
dataset = load_dataset("Kateht/VOYA_VSL")

print(dataset)

# Example output
DatasetDict({
    train: Dataset({
        features: ['sequences', 'labels'],
        num_rows: ...
    })
})

# Access a sample
sample = dataset["train"][0]
print(sample["sequences"].shape)  # (60, 1605)
print(sample["labels"])           # int label

# Split train/validation/test after loading
dataset = dataset["train"].train_test_split(test_size=0.2, seed=42)
```

## 🔖 Labels

The labels.json file maps class IDs to Vietnamese labels. Example:
```
{
  "class_0001": "địa chỉ (bắc)",
  "class_0002": "địa chỉ (nam)",
  "class_0003": "địa chỉ (trung)"
}
```

## 📜 Citation

If you use this dataset in your research, please cite:

```
@misc{voya_vsl_2025,
  author       = {Kateht et al.},
  title        = {VOYA Vietnamese Sign Language Dataset},
  year         = {2025},
  publisher    = {Hugging Face},
  howpublished = {\url{https://huggingface.co/datasets/Kateht/VOYA_VSL}}
}
```