Analyzing and improving genre and style classification in music through experiments

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dc.contributor.authorGhasemaghai, Zahra
dc.contributor.supervisorZhang, John Z.
dc.date.accessioned2015-01-30T19:37:16Z
dc.date.available2015-01-30T19:37:16Z
dc.date.issued2014
dc.degree.levelMastersen_US
dc.degree.levelMasters
dc.description.abstractMusic classification is a core task in the field of Music Information Retrieval (MIR). Classification refers to recognizing patterns in data. Music classification assigns genre, style, mood and etc. to each piece of music, to facilitate managing music data. It is an interesting topic in MIR with potential applications. There has been a considerable deal of attention focused on variety issues of music classification, such as selection appropriate feature sets, feature selection techniques, classification algorithm, etc. In this thesis, a series of empirical experiments are conducted to investigate and evaluate the genre and style classification in music. To validate our investigations and evaluations, several methods are proposed to analyze and interpret the results. In addition, we also design and implement an effective classification approach that obtains higher classification accuracy.en_US
dc.identifier.urihttps://hdl.handle.net/10133/3639
dc.language.isoen_CAen_US
dc.proquest.subject0984en_US
dc.proquest.subject0413en_US
dc.proquestyesYesen_US
dc.publisherLethbridge, Alta. : University of Lethbridge, Dept. of Mathematics and Computer Scienceen_US
dc.publisher.departmentDepartment of Mathematics and Computer Scienceen_US
dc.publisher.facultyArt and Scienceen_US
dc.relation.ispartofseriesThesis (University of Lethbridge. Faculty of Arts and Science)en_US
dc.subjectalgorithmsen_US
dc.subjectmusic classificationen_US
dc.subjectmusic dataen_US
dc.subjectmusic information retrievalen_US
dc.titleAnalyzing and improving genre and style classification in music through experimentsen_US
dc.typeThesisen_US
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