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Data Science Summer Colloquium Series: David Temperley

This talk is a featured presentation of the National Science Foundation Research Experience for Undergraduates (NSF REU) on Computational Methods for Understanding Music, Media, and Minds and is open to all faculty, staff, students and community members.

Lunch sponsored by Goergen Institute for Data Science. FREE to attend but register to ensure we order enough food.

TITLE: "Information Flow in Music"

ABSTRACT: The psychologist Daniel Berlyne proposed that a moderate level of complexity gives rise to an optimal aesthetic experience, and proposed quantifying complexity in terms of information. Similarly, psycholinguistic research has shown that a uniform, moderate rate of information flow is optimal for language comprehension. My recent research explores the extent to which this principle shapes music composition and performance. I will propose three strategies for smoothing information flow in music, and will examine evidence for these strategies in a variety of musical phenomena: rules of Renaissance composition, expressive piano performance, and the construction of classical melodies.

David Temperley is a music theorist, cognitive scientist, and composer. He received his PhD in music theory from Columbia University, followed by a post-doctoral fellowship at Ohio State University. Since 2000, he has been professor of music theory at Eastman School of Music. Temperley’s primary research area is computational modeling of music cognition; he has explored issues such as meter perception, key perception, harmonic analysis, and melodic expectation. You can hear Temperley’s compositions and learn more about his research at

Wednesday, July 11, 2018 at 12:00pm to 1:00pm

Wegmans Hall, Auditorium 1400
250 Hutchison Rd, Rochester, NY 14620

Event Type

Lectures and Talks, Conferences and Symposia


General Public, Faculty, Students, Alumni, Staff


data science, research

Goergen Institute for Data Science
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