arXiv AI By Maral Ebrahimzadeh, Gilberto Bernardes, Sebastian Stober

Emergent Tonal Structure in Learned Chord Embeddings and Its Relation to Tonal Tension

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arXiv Machine Learning
1d ago

CHORDONOMICON: A Dataset of 666,000 Songs and their Chord Progressions

Chordonomicon is a new dataset of over 666,000 song-level symbolic chord progressions, each annotated with structural parts such as verse, chorus, and bridge, as well as genre and release date. The dataset was compiled by scraping user-generated progressions from multiple sources and shows strong similarity to established prior datasets. The authors also provide a reproducible benchmark suite for next chord prediction, evaluating RNN, GRU, and LSTM models across various context windows and data scales, and find that structural part annotations consistently improve prediction performance.

By Spyridon Kantarelis, Ioannis Liolitsas, Konstantinos Thomas, Vassilis Lyberatos, Edmund Dervakos, Giorgos Stamou
arXiv Machine Learning
Jul 17

MIDI-RAE-JEPA: Hierarchical Representation Learning and Generation for Symbolic Music

arXiv:2607. 14537v1 Announce Type: cross Abstract: Rich internal representations of musical structure are essential for music understanding tasks such as machine-assisted music co-writing, yet self-supervised approaches for symbolic music representation remain underexplored, particularly those that encode the hierarchical multiscale nature of musical structures.

By Scott H. Hawley