Computational Musicology

Exploring music through data and algorithms

Computational musicology applies computational methods—from corpus statistics to machine learning and Artificial Intelligence and Music—to analyze musical corpora. This interdisciplinary field bridges computer science and musicology, enabling researchers to discover patterns, trace stylistic evolution, and quantify musical features at scales beyond human perception. This includes research at the intersection of Artificial Intelligence and Music, where machine learning helps to model musical structure and stylistic change.

Projects

Publications

Conference paper

Mapping the space of harmonic cadences between Brazilian choro, jazz and Anglophone popular music

Mauri Orsini Windholz, Fabian C. Moss

This paper reports on an experiment extends a methodology to analyze and compare harmonic progressions at moments of formal segmentation in different styles based on corpora of Roman numeral annotations, and deploys it to the styles of Brazilian choro, Anglophone popular and jazz music.

Talks