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Why apply a hierarchical predictive processing framework to music perception and performance?

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Michael, John and Wolf, Thomas (2014) Why apply a hierarchical predictive processing framework to music perception and performance? Empirical Musicology Review, 9 (3-4). pp. 177-182. doi:doi:10.18061/emr.v9i3-4.4613 ISSN 1559-5749.

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Official URL: http://dx.doi.org/10.18061/emr.v9i3-4.4613

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Abstract

In this commentary, we examine Schaefer’s proposal to apply a hierarchical predictive processing (HPP) framework to research on music perception and music performance. As we shall see, this proposal raises the possibility of enriching this research area with new theoretical and empirical resources from further afield. In order to tap the potential of such a project, it will be important to work towards the formulation of hypotheses that are uniquely generated by the HPP framework. We attempt to contribute to this project by specifying explanatory resources within the HPP framework that are well-suited to formulating such hypotheses, by articulating several novel questions that are generated by the attempt to apply the HPP framework to musical perception and performance, and by identifying potential challenges for such a project to address. We also provide reasons to expect that the HPP framework may be especially fruitful in the context of joint (musical) action.

Item Type: Journal Article
Subjects: M Music and Books on Music > ML Literature of music
Divisions: Faculty of Social Sciences > Philosophy
Library of Congress Subject Headings (LCSH): Musical perception
Journal or Publication Title: Empirical Musicology Review
Publisher: Ohio State University
ISSN: 1559-5749
Official Date: 2014
Dates:
DateEvent
2014Published
December 2014Accepted
November 2014Submitted
Volume: 9
Number: 3-4
Page Range: pp. 177-182
DOI: doi:10.18061/emr.v9i3-4.4613
Status: Peer Reviewed
Publication Status: Published
Access rights to Published version: Open Access (Creative Commons)
Date of first compliant deposit: 9 August 2016
Date of first compliant Open Access: 10 August 2016

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