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Areas of Research or Creative Practice: Music Perception & Cognition, Computational Musicology, Music Information Retrieval

Education

Ph.D in Music Theory & Cognition, Ohio State University, 2016
M.A. in Music Theory, University of British Columbia, 2008
B.Mus in Music theory and History, University of Toronto, 2004

Biography

Claire Arthur is an Associate Professor at the 17c��ҳ�� at the 17c��ҳ��, and holds an Adjunct Professor position in the School of Psychology. She is a teacher, musician, and foremost a scholar working in the fields of Music Perception and Cognition, Computational Musicology, and Music Information Retrieval. She received her PhD in Music Theory and Cognition from Ohio State working under David Huron. She completed her MA in Music Theory from the University of British Columbia, and her Bachelor’s degree at the University of Toronto. Claire is originally from Ontario, Canada.

Arthur’s research focuses on understanding how structural features of music such as melodic, harmonic, or formal organization influence cognitive processes such as memory, emotional responses, and aesthetic and neurological reward. Arthur leads the Computational and Cognitive Musicology Lab (CCML), co-led with Dr. Nat Condit-Schultz. Work in the CCML focuses on building novel datasets and corpora, as well as the coordinated analysis of both musical and human-generated data to gain insights to questions such as: Why are our favorite parts of our favorite songs so special?, What would make an AI-generated melody indistinguishable from a human-generated one?, What makes good, immersive music for video games? These types of questions are approached using human-subjects experiments as well as computational modeling of musical data. To help with this goal, we developed the software package which was inspired by David Huron’s humdrum toolkit, and carries much of the same functionality but ported into a modern software environment (R).

Arthur’s research has been published in over a dozen different journal publications and conference proceedings, including Music Perception, Music & Science, Journal of New Music Research, and the proceedings for the International Society for Music Information Retrieval (ISMIR).

Statement of Teaching Interest

Dr. Arthur teaches in the undergraduate Introduction to Audio Technologies sequence, as well as split graduate-undergraduate courses in Music Perception, Computational Musicology, and Audio Content Analysis. She also advises graduate research and undergraduate capstone projects. Her other teaching interests include various topics in basic and advanced music theory.

Statement of Research Interest

Dr. Arthur conducts an interdisciplinary research practice that combines computational musicology, music perception and cognition, and music information retrieval. Her research largely focuses on modeling musical structure from a statistical perspective using symbolic musical data, as well as examining the cognitive and behavioral correlates of those structures, especially as it relates to musical expectations, emotional responses, and memory.

Recent Scholarly Work

• Alexander Lerch, Claire Arthur, Nick Bryan-Kinns, Corey Ford, Qianyi Sun, and Ashvala
  Vinay. (2025) “Survey on the Evaluation of Generative Models in Music.” ACM Computing Survey,
  58(4):99:1–99:36.
• Claire Arthur. (2024). “Harmonic expectancy violations: Testing the effects of familiarity, lead-in
  time, and ecological validity.” Psychology of Music, 53(6), 947–968.
• Claire Arthur. (2023) “Why do songs get “stuck in our heads”? towards a theory for explaining
  �𲹰��ɴǰ�����.” Music & Science, 6.
• Noel Alben and Claire Arthur. (2023). “Pupil Dilation as a Function of Pitch Discrimination Difficulty:
  A Replication of Kahneman and Beatty, 1967.” Attention, Perception & Psychophysics, 86, 1435–1444. 
• Claire Arthur and Nathaniel Condit-Schultz. (2023). “The Coordinated Corpus of Popular Musics
  (CoCoPops): A Meta-Corpus of Melodic and Harmonic Transcriptions.” In Proceedings of the
  24th Society of Music Information Retrieval Conference (ISMIR), pages 239–246.
• Claire Arthur, Frank Lehman, and John McNamara. (2022). “Presenting the SWTC: A Symbolic
  Corpus of Themes from John Williams’ Star Wars Episodes I-IX.” Empirical Musicology
  Review, 17(2).