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# ArtifactNet-Real
Real (human-created) music dataset for AI-generated music detection research.
## Overview
| Split | Songs | Segments | Size |
|-------|-------|----------|------|
| Train | 15,546 | 70,463 | 47GB |
| Val | 1,943 | 8,075 | 5.4GB |
| Test | 1,944 | 8,384 | 5.6GB |
| **Total** | **19,433** | **86,922** | **~58GB** |
## Format
- **Audio**: WAV, 44.1kHz, Stereo
- **Segment Duration**: 4 seconds
- **Hop Size**: 2 seconds (50% overlap)
## Structure
```
ArtifactNet-Real/
├── README.md
├── metadata.json # Song lists per split
├── train/{song_id}/seg_XXXX.wav
├── val/{song_id}/seg_XXXX.wav
└── test/{song_id}/seg_XXXX.wav
```
## Usage
This dataset provides **Real** (human-created) music samples for training AI music detection models.
To generate Demucs residuals:
```python
from demucs.pretrained import get_model
from demucs.apply import apply_model
model = get_model('htdemucs')
# residual = original - sum(sources)
```
## License
CC-BY-NC 4.0 (Non-commercial use)
## Citation
```bibtex
@dataset{artifactnet_real_2026,
title={ArtifactNet-Real: Real Music Dataset for AI Detection},
author={...},
year={2026},
url={...}
}
```
## Related
- **ArtifactNet**: AI-generated music detection framework
- **Paper**: [TBD]
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