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  Time-course variation of statistics embedded in music: Corpus study on implicit learning and knowledge

Daikoku, T. (2018). Time-course variation of statistics embedded in music: Corpus study on implicit learning and knowledge. PLoS One, 13(5): e0196493. doi:10.1371/journal.pone.0196493.

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Item Permalink: http://hdl.handle.net/21.11116/0000-0001-462D-F Version Permalink: http://hdl.handle.net/21.11116/0000-0003-9AC8-E
Genre: Journal Article

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Daikoku(2018).pdf (Publisher version), 2MB
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 Creators:
Daikoku, Tatsuya1, Author              
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1Department Neuropsychology, MPI for Human Cognitive and Brain Sciences, Max Planck Society, ou_634551              

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 Abstract: Learning and knowledge of transitional probability in sequences like music, called statistical learning and knowledge, are considered implicit processes that occur without intention to learn and awareness of what one knows. This implicit statistical knowledge can be alternatively expressed via abstract medium such as musical melody, which suggests this knowledge is reflected in melodies written by a composer. This study investigates how statistics in music vary over a composer’s lifetime. Transitional probabilities of highest-pitch sequences in Ludwig van Beethoven’s Piano Sonata were calculated based on different hierarchical Markov models. Each interval pattern was ordered based on the sonata opus number. The transitional probabilities of sequential patterns that are musical universal in music gradually decreased, suggesting that time-course variations of statistics in music reflect time-course variations of a composer’s statistical knowledge. This study sheds new light on novel methodologies that may be able to evaluate the time-course variation of composer’s implicit knowledge using musical scores.

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Language(s): eng - English
 Dates: 2017-06-272018-04-142018-05-09
 Publication Status: Published online
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Method: Peer
 Identifiers: DOI: 10.1371/journal.pone.0196493
PMID: 29742112
PMC: PMC5942787
Other: eCollection 2018
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Funding program : Grant-in-Aid for Scientific Research
Funding organization : Nakayama Foundation for Human Science
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Funding program : -
Funding organization : Kawai Foundation for Sound Technology and Music

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Title: PLoS One
Source Genre: Journal
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Publ. Info: San Francisco, CA : Public Library of Science
Pages: - Volume / Issue: 13 (5) Sequence Number: e0196493 Start / End Page: - Identifier: ISSN: 1932-6203
CoNE: https://pure.mpg.de/cone/journals/resource/1000000000277850