An empirical evaluation of computational and perceptual multi-label genre classification on music / Christopher Sanden

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dc.contributor.authorSanden, Christopher
dc.contributor.authorUniversity of Lethbridge. Faculty of Arts and Science
dc.contributor.supervisorZhang, John Z.
dc.date.accessioned2012-02-06T23:15:41Z
dc.date.available2012-02-06T23:15:41Z
dc.date.issued2010
dc.degree.levelMasters
dc.descriptionviii, 87 leaves ; 29 cmen_US
dc.description.abstractAutomatic 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. iien_US
dc.identifier.urihttps://hdl.handle.net/10133/2602
dc.language.isoen_USen_US
dc.publisherLethbridge, Alta. : University of Lethbridge, Dept. of Mathematics and Computer Science, c2010en_US
dc.publisher.departmentDepartment of Mathematics and Computer Scienceen_US
dc.publisher.facultyArts and Scienceen_US
dc.relation.ispartofseriesThesis (University of Lethbridge. Faculty of Arts and Science)en_US
dc.subjectInformation storage and retrieval systems -- Musicen_US
dc.subjectMusic -- Data processingen_US
dc.subjectDissertations, Academicen_US
dc.titleAn empirical evaluation of computational and perceptual multi-label genre classification on music / Christopher Sandenen_US
dc.typeThesisen_US
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