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Developing and evaluating computational models of musical style

Collins, Tom; Laney, Robin; Willis, Alistair and Garthwaite, Paul H. (2016). Developing and evaluating computational models of musical style. Artificial Intelligence for Engineering Design, Analysis and Manufacturing, 30(01) pp. 16–43.

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Stylistic composition is a creative musical activity, in which students as well as renowned composers write according to the style of another composer or period. We describe and evaluate two computational models of stylistic composition, called Racchman-Oct2010 (random constrained chain of Markovian nodes, October 2010) and Racchmaninof-Oct2010 (Racchman with inheritance of form). The former is a constrained Markov model, and the latter embeds this model in an analogy based design system. Racchmaninof-Oct2010 applies a pattern discovery algorithm called SIACT and a perceptually validated formula for rating pattern importance, to guide the generation of a new target design from an existing source design. A listening study is reported concerning human judgments of music excerpts that are, to varying degrees, in the style of mazurkas by Frédéric Chopin (1810–1849). The listening study acts as an evaluation of the two computational models and a third, benchmark system, called Experiments in Musical Intelligence. Judges’ responses indicate that some aspects of musical style, such as phrasing and rhythm, are being modeled effectively by our algorithms. Judgments are also used to identify areas for future improvements. We discuss the broader implications of this work for the fields of engineering and design, where there is potential to make use of our models of hierarchical repetitive structure.

Item Type: Journal Item
Copyright Holders: 2015 Cambridge University Press
ISSN: 1469-1760
Project Funding Details:
Funded Project NameProject IDFunding Body
Not SetNot SetEPSRC (Engineering and Physical Sciences Research Council)
Keywords: Computational Model; Musical Creativity; Stylistic Composition
Academic Unit/School: Faculty of Science, Technology, Engineering and Mathematics (STEM) > Computing and Communications
Faculty of Science, Technology, Engineering and Mathematics (STEM)
Faculty of Science, Technology, Engineering and Mathematics (STEM) > Mathematics and Statistics
Research Group: Centre for Research in Computing (CRC)
Item ID: 46071
Depositing User: Danielle Lilly
Date Deposited: 14 Apr 2016 13:32
Last Modified: 12 Jul 2020 16:30
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