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dc.contributor.authorR. Brown, Andrewen_US
dc.contributor.authorGifford, Tobyen_US
dc.contributor.editorSteven M. Demorest, Steven J. Morrison & Patricia S. Campbellen_US
dc.description.abstractWe have developed a new experimental method for interrogating statistical theories of music perception by implementing these theories as generative music algorithms. We call this method Generation in Context. This method differs from most experimental techniques in music perception in that it incorporates aesthetic judgments. Generation In Context is designed to measure percepts for which the musical context is suspected to play an important role. In particular the method is suitable for the study of perceptual parameters which are temporally dynamic. We outline a use of this approach to investigate David Temperley's (2007) probabilistic melody model, and provide some provisional insights as to what is revealed about the model. We suggest that Temperley's model could be improved by dynamically modulating the probability distributions according to the changing musical context.en_US
dc.publisherUniversity of Washingtonen_US
dc.publisher.placeSeattle, WA, USAen_US
dc.relation.ispartofconferencename11th International Conference on Music Perception and Cognitionen_US
dc.relation.ispartofconferencetitleProceedings of the 11th International Conference on Music Perception and Cognitionen_US
dc.relation.ispartoflocationSeattle, USAen_US
dc.subject.fieldofresearchMusic Compositionen_US
dc.titleInterrogating Statistical Models of Music Perceptionen_US
dc.typeConference outputen_US
dc.type.descriptionE1 - Conference Publications (HERDC)en_US
dc.type.codeE - Conference Publicationsen_US
gro.hasfulltextNo Full Text

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    Contains papers delivered by Griffith authors at national and international conferences.

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