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dc.contributor.supervisor Zhang, John Z. Sanden, Christopher University of Lethbridge. Faculty of Arts and Science 2012-02-06T23:15:41Z 2012-02-06T23:15:41Z 2010
dc.description viii, 87 leaves ; 29 cm en_US
dc.description.abstract Automatic music genre classi cation is a high-level task in the eld of Music Information Retrieval (MIR). It refers to the process of automatically assigning genre labels to music for various tasks, including, but not limited to categorization, organization and browsing. This is a topic which has seen an increase in interest recently as one of the cornerstones of MIR. However, due to the subjective and ambiguous nature of music, traditional single-label classi cation is inadequate. In this thesis, we study multi-label music genre classi cation from perceptual and computational perspectives. First, we design a set of perceptual experiments to investigate the genre-labelling behavior of individuals. The results from these experiments lead us to speculate that multi-label classi cation is more appropriate for classifying music genres. Second, we design a set of computational experiments to evaluate multi-label classi cation algorithms on music. These experiments not only support our speculation but also reveal which algorithms are more suitable for music genre classi cation. Finally, we propose and examine a group of ensemble approaches for combining multi-label classi cation algorithms to further improve classi cation performance. ii en_US
dc.language.iso en_US en_US
dc.publisher Lethbridge, Alta. : University of Lethbridge, Dept. of Mathematics and Computer Science, c2010 en_US
dc.relation.ispartofseries Thesis (University of Lethbridge. Faculty of Arts and Science) en_US
dc.subject Information storage and retrieval systems -- Music en_US
dc.subject Music -- Data processing en_US
dc.subject Dissertations, Academic en_US
dc.title An empirical evaluation of computational and perceptual multi-label genre classification on music / Christopher Sanden en_US
dc.type Thesis en_US
dc.publisher.faculty Arts and Science en_US
dc.publisher.department Department of Mathematics and Computer Science en_US Masters

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