P4-12: FiloBass: A Dataset and Corpus Based Study of Jazz Basslines

Xavier Riley (C4DM)*, Simon Dixon (Queen Mary University of London)

Subjects (starting with primary): Evaluation, datasets, and reproducibility -> novel datasets and use cases ; MIR tasks -> music transcription and annotation ; Computational musicology -> digital musicology

Presented In Person: 4-minute short-format presentation

Abstract:

We present FiloBass: a novel corpus of music scores and annotations which focuses on the important but often overlooked role of the double bass in jazz accompaniment. Inspired by recent works that shed light on the role of the soloist, we offer a collection of 48 manually verified transcriptions of professional jazz bassists, comprising over 50,000 note events, which are based on the backing tracks used in the FiloSax dataset. For each recording we provide audio stems, scores, performance-aligned MIDI and associated metadata for beats, downbeats, chord symbols and markers for musical form.

We then use FiloBass to enrich our understanding of jazz bass lines, by conducting a corpus-based musical analysis with a contrastive study of existing instructional methods. Together with the original FiloSax dataset, our work represents a significant step toward a fully annotated performance dataset for a jazz quartet setting. By illuminating the critical role of the bass in jazz, this work contributes to a more nuanced and comprehensive understanding of the genre.

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