GuitarSet¶
Summary¶
~3 hours of solo acoustic guitar recordings with comprehensive annotations: note-level (pitch, onset, offset), string-level, fret-level, and playing technique annotations. Recorded with hexaphonic pickup providing per-string audio alongside mono microphone. 360 excerpts across 6 players and multiple styles. JAMS annotation format. Presented at ISMIR 2018 (150+ citations). GitHub: marl/GuitarSet (160 stars).
Key Claims¶
- Hexaphonic pickup provides ground-truth per-string audio for training separation/transcription models
- JAMS format standardizes multi-level annotations (notes, strings, frets, techniques)
- 3 hours sufficient for training initial deep learning models (as demonstrated by TabCNN)
- Dataset enables both transcription and source separation research on guitar
Relevance to Banjo¶
The blueprint for creating "BanjoSet." Every aspect of the GuitarSet methodology translates to banjo: - Per-string pickup (piezo or magnetic split pickup on banjo) provides ground-truth string-level audio - JAMS annotation format works for any stringed instrument - Same annotation schema: pitch, onset, offset, string, fret, technique - ~3 hours likely sufficient for initial banjo transcription model training
A banjo dataset should additionally capture: drone string activity (5th string, almost always open), roll patterns, and bluegrass-specific techniques (hammer-on, pull-off, slide, choke).
Related¶
- ../entities/guitarset — entity page
- ../entities/tabcnn — model trained on GuitarSet
- ../concepts/musicxml-tab-notation — output format
- ../concepts/synthetic-mixing-pipelines — data augmentation strategy