Ashley Burgoyne

Assistant Professor in Computational Musicology

John Ashley Burgoyne is the Lecturer in Computational Musicology at the University of Amsterdam and a researcher in the Music Cognition Group at the Institute for Logic, Language, and Computation. Cross-appointed in Musicology and Artificial Intelligence, he is interested in understanding musical behaviour at the audio level, using large-scale experiments and audio corpora. His McGill–Billboard corpus of time-aligned chord and structure transcriptions has served as a backbone for audio chord estimation techniques. His ‘Hooked-on Music’ project reached hundreds of thousands of participants in almost every country on Earth while collecting data to understand long-term musical memory. Currently, he is working through the Amsterdam Music Lab to understand what people are hearing – and what they are ignoring – while they stream music every day.

Latest publications

Korsmit, I. R., Burgoyne, J. A., & Honing, H. (2017). If You Wanna Be My Lover … A Hook Discovery Game to Uncover Individual Differences in Long-term Musical Memory. In E. Van Dijck (Ed.), Proceedings of the 25th Anniversary Conference of the European Society for the Cognitive Sciences of Music (pp. 106–111). Ghent University.
Mooren, N., Burgoyne, J. A., & Honing, H. (2017). Investigating grouping behaviour of dancers in a silent disco using overhead video capture. In E. Van Dijck (Ed.), Proceedings of the 25th Anniversary Conference of the European Society for the Cognitive Sciences of Music (pp. 142–149). Ghent University.

Media attention

Kan AI de winnaar van het Songfestival voorspellen?NPO1
What makes music catchy?University of the Netherlands
Ashley Burgoyne on the science and mystery of listeningILLC Blog
Ashley Burgoyne en Janne Spijkervet over VPRO's AI SongfestivalNPO Radio 1
Ashley Burgoyne over kortere aandachtsspanne bij
Over songfestival inzendingenNTR Kennis van Nu
Ashley Burgoyne over inzending songfestivalFolia
Ashley Burgoyne on #HookedDiverse media


Computational Musicology
BA Musicology6 ECTSCode: 115215146Y
How Music Works I: Computational and Cognitive Perspectives
MA Musicology6 ECTSCode: 145415346Y
Tweedejaarsproject BSc KI
BSc Kunstmatige Intelligentie6 ECTSCode: 5082TWBK5Y
Quantitive Methods in Musicology
BA Musicology3 ECTS
Onderzoeksproject Muziekwetenschap II
BA Musicology6 ECTSCode: 115221206Y


Ivan Bobrov
MSc Computational Science, UvA2021
Ada Örken
MSc Brain & Cognitive Sciences, UvA2021
Lisa Veenstra
MA Music Studies2020
Henk Jacobs
MA Music Studies2020
Lars Mangel
MA Music Studies2020
MSc Artificial Intelligence2020
Leanne Kuiper
MSc Brain and Cognitive Sciences2020
Ada Örken
MSc Brain and Cognitive Sciences2020
Kostas Giannos
MA Music Studies, UvA2019
MA Music Studies2019
Sem Dekkers
MA Musicology, UvA2018
Lucija Fric
MA Musicology, UvA + VU2018
Joy Huiskens
MA Musicology, UvA2018
Tiarma Witte
MSc Brain & Cognitive Sciences, UvA2017
Iza Korsmit
MSc Brain & Cognitive Sciences, UvA2016
Nelson Mooren
MSc Brain & Cognitive Sciences, UvA2016
Oisín Ó Cualáin
Master Musicology, UvA2016
Albertine Holterman
Master Musicology, UvA2016
Lisanne Bogaard
Master Clinical Psychology, VU2016
Jurre Thuis
MA Musicology, UvA2015
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