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• W1916682500 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." @default.
• W1916682500 created "2016-06-24" @default.
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• W1916682500 date "2015-09-01" @default.
• W1916682500 modified "2023-10-18" @default.
• W1916682500 title "Classification and Generation of Composer-Specific Music Using Global Feature Models and Variable Neighborhood Search" @default.
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• W1916682500 doi "https://doi.org/10.1162/comj_a_00316" @default.
• W1916682500 hasPublicationYear "2015" @default.
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