Perceptual basis of evolving Western musical styles

Autores
Shifres, Favio; Rodríguez Zivic, Pablo H.; Cecchi, Guillermo A.
Año de publicación
2013
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
The brain processes temporal statistics to predict future events and to categorize perceptual objects. These statistics, called expectan- cies, 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 distri- bution 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.
Facultad de Bellas Artes
Materia
Bellas Artes
Música
pattern recognition; psychology; computational cognition; culturomics
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by-nc-nd/4.0/
Repositorio
SEDICI (UNLP)
Institución
Universidad Nacional de La Plata
OAI Identificador
oai:sedici.unlp.edu.ar:10915/53310

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network_name_str SEDICI (UNLP)
spelling Perceptual basis of evolving Western musical stylesShifres, FavioRodríguez Zivic, Pablo H.Cecchi, Guillermo A.Bellas ArtesMúsicapattern recognition; psychology; computational cognition; culturomicsThe brain processes temporal statistics to predict future events and to categorize perceptual objects. These statistics, called expectan- cies, 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 distri- bution 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.Facultad de Bellas Artes2013-06info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionArticulohttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfhttp://sedici.unlp.edu.ar/handle/10915/53310enginfo:eu-repo/semantics/altIdentifier/url/http://www.pnas.org/content/110/24/10034.full.pdfinfo:eu-repo/semantics/altIdentifier/issn/0027-8424info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-nd/4.0/Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-09-29T11:04:59Zoai:sedici.unlp.edu.ar:10915/53310Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-29 11:04:59.67SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv Perceptual basis of evolving Western musical styles
title Perceptual basis of evolving Western musical styles
spellingShingle Perceptual basis of evolving Western musical styles
Shifres, Favio
Bellas Artes
Música
pattern recognition; psychology; computational cognition; culturomics
title_short Perceptual basis of evolving Western musical styles
title_full Perceptual basis of evolving Western musical styles
title_fullStr Perceptual basis of evolving Western musical styles
title_full_unstemmed Perceptual basis of evolving Western musical styles
title_sort Perceptual basis of evolving Western musical styles
dc.creator.none.fl_str_mv Shifres, Favio
Rodríguez Zivic, Pablo H.
Cecchi, Guillermo A.
author Shifres, Favio
author_facet Shifres, Favio
Rodríguez Zivic, Pablo H.
Cecchi, Guillermo A.
author_role author
author2 Rodríguez Zivic, Pablo H.
Cecchi, Guillermo A.
author2_role author
author
dc.subject.none.fl_str_mv Bellas Artes
Música
pattern recognition; psychology; computational cognition; culturomics
topic Bellas Artes
Música
pattern recognition; psychology; computational cognition; culturomics
dc.description.none.fl_txt_mv The brain processes temporal statistics to predict future events and to categorize perceptual objects. These statistics, called expectan- cies, 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 distri- bution 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.
Facultad de Bellas Artes
description The brain processes temporal statistics to predict future events and to categorize perceptual objects. These statistics, called expectan- cies, 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 distri- bution 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.
publishDate 2013
dc.date.none.fl_str_mv 2013-06
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