Perceptual basis of evolving Western musical styles |
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Authors: | Pablo H. Rodriguez Zivic Favio Shifres Guillermo A. Cecchi |
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Affiliation: | aComputer Science Department, University of Buenos Aires, 1428 Buenos Aires, Argentina;;bLaboratory for Music Experience Study, Faculty of Fine Arts, National University of La Plata, 1900 La Plata, Argentina; and;cComputational Biology Center, T. J. Watson IBM Research Center, Yorktown Heights, NY, 10598 |
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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. |
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Keywords: | pattern recognition psychology computational cognition culturomics |
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