title: Perceptual basis of evolving Western musical styles.
abstract: The brain processes temporal statistics to predict future events and to categorize perceptual objects. These statistics, called expectancies, are found in music perception, and they span a variety of different features and time scales. Specifically, there is evidence that music perception involves strong expectancies regarding the distribution of a melodic interval, namely, the distance between two consecutive notes within the context of another. The recent availability of a large Western music dataset, consisting of the historical record condensed as melodic interval counts, has opened new possibilities for data-driven analysis of musical perception. In this context, we present an analytical approach that, based on cognitive theories of music expectation and machine learning techniques, recovers a set of factors that accurately identifies historical trends and stylistic transitions between the Baroque, Classical, Romantic, and Post-Romantic periods. We also offer a plausible musicological and cognitive interpretation of these factors, allowing us to propose them as data-driven principles of melodic expectation.
authors.affiliation: Computer Science Department, University of Buenos Aires, 1428 Buenos Aires, Argentina. prodriguez@dc.uba.ar
authors.forename: Pablo H
authors.initials: PH
authors.lastname: Rodriguez Zivic
authors.forename: Favio
authors.initials: F
authors.lastname: Shifres
authors.forename: Guillermo A
authors.initials: GA
authors.lastname: Cecchi
mesh_terms: D000161:Acoustic Stimulation / Q000379:methods / Q000639:trends; D000465:Algorithms; D001307:Auditory Perception / Q000502:physiology*; D003071:Cognition / Q000502:physiology*; D003198:Computer Simulation; D006801:Humans; D008962:Models, Theoretical; D009146:Music; D010898:Pitch Perception / Q000502:physiology*
keywords: computational cognition; culturomics; pattern recognition; psychology