Datasets:
license: cc-by-nc-sa-4.0
tags:
- music
- vocal-transcription
- melody
- pitch-detection
pretty_name: Vocal Melody Transcription Dataset v1
Vocal Melody Transcription Dataset v1
Training data for a monophonic vocal melody transcription model. The model uses a ROSVOT-style architecture (MERT encoder → U-Net w/ Conformer bottleneck → onset/pitch/frame heads) and is designed to receive Demucs v4-separated vocal audio at inference time.
Datasets
| Source | Tracks | Description |
|---|---|---|
| MIR-ST500 | 385 | Pop songs with manual onset/offset/pitch annotations |
| DALI | ~4,927 | Large-scale vocal annotations aligned to audio (10 batch tars) |
| MedleyDB | 107 | Multitrack recordings with Melody2 F0→note converted annotations |
| Total | ~5,420 | Matched audio+label pairs across all sources |
All audio is resampled to 24kHz mono WAV, peak-normalized to -1dB. Labels are unified CSV format: onset_sec, offset_sec, pitch_midi, pitch_hz, source_dataset.
Files on this repo
| File | Size | Contents |
|---|---|---|
vocal_v1.tar |
~1.3GB | MIR-ST500 processed audio + labels |
vocal_v1_dali_batch{1-10}.tar |
~4GB each | DALI processed audio + labels (10 batches) |
vocal_v1_medleydb.tar |
~915MB | MedleyDB processed audio (24kHz) + note-level labels |
MedleyDB_v1.tar |
~8.8GB | Raw MedleyDB V1: 122 MIX wavs + 116 vocal stems (not used directly in training pipeline) |
oneshots.tar |
~972MB | 1,204 curated vocal oneshots for vocal bleed augmentation |
vocal_v1_augmented.tar |
— | OBSOLETE (on-the-fly augmentation used instead) |
Augmentation (on-the-fly)
Applied during training only (never to val/test):
- Pitch shift: ±4 semitones (label-aware — adjusts pitch annotations)
- Time stretch: 0.85x–1.15x
- Noise injection: SNR 10–40dB
- Vocal bleed: overlay random oneshots at SNR 25–40dB
- Downsample-resample: through 16kHz/22.05kHz
- Random EQ: 3-band, ±3dB gain
Training Pipeline
run.sh (SLURM) auto-downloads all tars (skipping augmented and raw MedleyDB_v1), extracts to data/, rebuilds train/val/test splits stratified by source (seed 42), then trains with on-the-fly augmentation.
Label Format
onset_sec, offset_sec, pitch_midi, pitch_hz, source_dataset
0.52, 0.89, 60.0, 261.63, mir_st500
Pitch targets use bin offset: bin 0 = unvoiced, bin 1 = MIDI 21 (A0), so pitch_bin = midi_note - 21 + 1.