Title
Classification and generation of composer-specific music using global feature models and variable neighborhood search Classification and generation of composer-specific music using global feature models and variable neighborhood search
Author
Faculty/Department
Faculty of Applied Economics
Publication type
article
Publication
Cambridge, Mass. ,
Subject
Computer. Automation
Art
Source (journal)
Computer music journal. - Cambridge, Mass.
Volume/pages
39(2015) :3 , p. 71-91
ISSN
0148-9267
ISI
000361183900005
Carrier
E
Target language
English (eng)
Full text (Publishers DOI)
Affiliation
University of Antwerp
Abstract
In this article a number of musical features are extracted from a large musical database and these were subsequently used to build four composer-classification models. The first two models, an if-then rule set and a decision tree, result in an understanding of stylistic differences between Bach, Haydn, and Beethoven. The other two models, a logistic regression model and a support vector machine classifier, are more accurate. The probability of a piece being composed by a certain composer given by the logistic regression model is integrated into the objective function of a previously developed variable neighborhood search algorithm that can generate counterpoint. The result is a system that can generate an endless stream of contrapuntal music with composer-specific characteristics that sounds pleasing to the ear. This system is implemented as an Android app called FuX.
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Full text (open access)
https://repository.uantwerpen.be/docman/irua/d56e77/127842_2016_03_11.pdf
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