Perceptual basis of evolving Western musical styles
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 s...
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2013
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| Acceso en línea: | https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_00278424_v110_n24_p10034_RodriguezZivic http://hdl.handle.net/20.500.12110/paper_00278424_v110_n24_p10034_RodriguezZivic |
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paper:paper_00278424_v110_n24_p10034_RodriguezZivic |
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paper:paper_00278424_v110_n24_p10034_RodriguezZivic2023-06-08T14:54:28Z Perceptual basis of evolving Western musical styles Computational cognition Culturomics Pattern recognition Psychology article cluster analysis cognition history machine learning music music perception perception priority journal probability computational cognition culturomics pattern recognition psychology Acoustic Stimulation Algorithms Auditory Perception Cognition Computer Simulation Humans Models, Theoretical Music Pitch Perception 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. 2013 https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_00278424_v110_n24_p10034_RodriguezZivic http://hdl.handle.net/20.500.12110/paper_00278424_v110_n24_p10034_RodriguezZivic |
| institution |
Universidad de Buenos Aires |
| institution_str |
I-28 |
| repository_str |
R-134 |
| collection |
Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA) |
| topic |
Computational cognition Culturomics Pattern recognition Psychology article cluster analysis cognition history machine learning music music perception perception priority journal probability computational cognition culturomics pattern recognition psychology Acoustic Stimulation Algorithms Auditory Perception Cognition Computer Simulation Humans Models, Theoretical Music Pitch Perception |
| spellingShingle |
Computational cognition Culturomics Pattern recognition Psychology article cluster analysis cognition history machine learning music music perception perception priority journal probability computational cognition culturomics pattern recognition psychology Acoustic Stimulation Algorithms Auditory Perception Cognition Computer Simulation Humans Models, Theoretical Music Pitch Perception Perceptual basis of evolving Western musical styles |
| topic_facet |
Computational cognition Culturomics Pattern recognition Psychology article cluster analysis cognition history machine learning music music perception perception priority journal probability computational cognition culturomics pattern recognition psychology Acoustic Stimulation Algorithms Auditory Perception Cognition Computer Simulation Humans Models, Theoretical Music Pitch Perception |
| description |
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. |
| title |
Perceptual basis of evolving Western musical styles |
| 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 |
| publishDate |
2013 |
| url |
https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_00278424_v110_n24_p10034_RodriguezZivic http://hdl.handle.net/20.500.12110/paper_00278424_v110_n24_p10034_RodriguezZivic |
| _version_ |
1768545132655673344 |