README.md

metadata

title: ArtifactNet
emoji: 🎵
colorFrom: yellow
colorTo: blue
sdk: gradio
sdk_version: 4.44.0
app_file: app.py
python_version: '3.10'
pinned: true
license: other
short_description: AI-generated music detection (v9.4 Forensic CNN + HPSS)
hardware: cpu-basic
models:
  - intrect/artifactnet-models

ArtifactNet — AI Music Forensic Detector

Upload a track (WAV / MP3 / FLAC, ≤100 MB, ≤5 min). ArtifactNet analyses spectral + harmonic-percussive forensic features and returns a per-segment P(AI) distribution.

• Backbone: STFT → U-Net artifact residual → HPSS → 7-channel features → CNN
• Verdict: energy-weighted median across 4-second segments
• Runtime: ONNX Runtime on HF Space CPU (~30–60 s per 4-minute track)

Paper

ArtifactNet: Forensic Detection of AI-Generated Music via HPSS and Residual Analysis — arXiv:2604.16254.

Links

• Production dashboard: dash.intrect.io
• Pricing / API: intrect.io

Notes

• Short files (<60 s) have fewer segments and lower confidence.
• Mono input disables stereo phase features.
• Heavily processed audio (bitcrushing, vinyl rips) may affect results.
• YouTube / URL intake is disabled on this Space — use the dashboard for batch processing.
• Only the ONNX graphs (inference-only, no training metadata) are published; the original PyTorch checkpoints remain private.