Why do humans make music, and how do they do it? Why are we a musical species? These are the questions that motivate my research. I use computational methods to study how musical traditions differ. Mapping the diversity of musics across the globe, is a key step in understanding the cultural evolution of musics.

The cover of my PhD dissertation visualizes which basic rhythmic motifs can be found in a recording of Malian jembe drumming, in a so-called rhythm triangle (see page 81)

Dissertation: Measuring musics

On Friday 23 February 2024, I defended my doctoral dissertation Measuring musics: Notes on modes, motifs, and melodies. The dissertation consists of several studies that try to measure properties of musical traditions. In the same way linguists have compared languages to work out how they are related, what properties are common, and which are rare, musicologists have compared musical traditions or musics. To do so, you somehow need to measure the properties you are interested in. My dissertation develops computational methods to measure musics. It discusses, amongst others, modes in plainchant, inventories of rhythmic and melodic motifs, and shapes of melodies.

Curious? Read the feature Bruno van Wayenburg wrote for NRC or have a look at the dissertation (PDF, 27MB).


My academic life has been closely connected to the University of Amsterdam: where I did my bachelors (Bèta-gamma) and masters (Logic), both with a major in mathematics. I then went on to do a PhD in computational musicology with Jelle Zuidema, John Ashley Burgoyne and Henkjan Honing at the Institute for Logic, Language and Computation. Currently, I am a lecturer in cognition and computation at the department of musicology at the Univeristy of Amsterdam, and affiliated to the Music Cognition Group.

For more details, have a look at my CV.

Research projects

Algo PärtAlgorithmic recompositions of the music of Arvo Pärt (to be made public soon)
Neural chantComposing plainchant with an LSTM (to be made public soon)
Rhythm trianglesVisualize rhythm in music and animal sounds using rhythm triangles.
Melody squaresA project visualizing which melodic motifs can be found in a collection of melodies.
Shapes of musicHow to best describe the shapes of melodic phrases in musics from across the globe? This paper adresses precisely that: contour typology.
Social bonding or credible signaling?Two target articles in BBS discussed the origins of musicality. We asked and visualized where the commentators would position themselves in this debate.
Cosine contoursAn ISMIR paper on a novel representation for melodic contours based on cosines.
CatafolkCatafolk: A catalogue of folk music corpora for computational ethnomusicology, presented at SysMus21.
Mode classification and natural units in plainchantAn ISMIR paper that classifies mode in plainchant and by doing so finds evidence for a 'natural' units of chant. This paper won the best multi/interdisciplinary research award!
GregoBase CorpusA large plainchant corpus based on GregoBase
Cantus CorpusA large plainchant corpus based on the Cantus database
Bayesian Language GamesA project that unifies iterated learning with naming games in a new Bayesian language game (MSc thesis)
PainterAn animated drawing environment intended for online iterated learning experiments.
UvA speech to song datasetUvA speech to song dataset, presented at ICMPC 2016 (dataset to be made public soon)
Analogy ColouringA novel variant of the pictorial analogy task, that asks subjects to colour drawings in the same way (student project).


Cornelissen, B. (2024). Measuring Musics: Notes on Modes, Motifs, and Melodies [Phdthesis]. University of Amsterdam.
Cornelissen, B., Zuidema, W., & Burgoyne, J. A. (2021a). Catafolk: Cataloguing Folk Music Datasets for Comparative Musicology. International Conference of Students of Systematic Musicology.
Cornelissen, B., Zuidema, W., & Burgoyne, J. A. (2021b). Cosine Contours: a Multipurpose Representation for Melodies. Proceedings of the 22th International Conference on Music Information Retrieval.
Cornelissen, B., Zuidema, W., & Burgoyne, J. A. (2021c). Fixing Huron’s Contour Typology. Poster presented at the Low Countries Music Network Meeting.
Cornelissen, B., Zuidema, W., & Burgoyne, J. A. (2021d). Musical Modes as Statistical Modes: Classifying Modi in Gregorian Chant. Proceedings of the 6th International Conference on Analytical Approaches to World Music.
Cornelissen, B., Zuidema, W., & Burgoyne, J. A. (2020a). Mode Classification and Natural Units in Plainchant. Proceedings of the 21th International Conference on Music Information Retrieval, 869–875.
Cornelissen, B., Zuidema, W., & Burgoyne, J. A. (2020b). Studying Large Plainchant Corpora Using chant21. 7th International Conference on Digital Libraries for Musicology, 5.
Cornelissen, B. (2017). Bayesian Language Games: Unifying and Evaluating Agent-Based Models of Horizontal and Vertical Language Evolution [Master’s thesis]. University of Amsterdam.
Cornelissen, B., & Zuidema, W. (2017). Unifying Horizontal and Vertical Interactions in the Bayesian Naming Game. Poster presented at the workshop Minds, Mechanisms, and Interaction in the Evolution of Language.
Cornelissen, B., Sadakata, M., & Honing, H. (2016). Categorization in the Speech to Song Transformation (STS). Proceedings of the 14th International Conference on Music Perception and Cognition, 386.
Cornelissen, B. (2014). Non-measurable Sets [Bachelor’s thesis]. University of Amsterdam.