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dc.contributor.supervisor Zhang, John Z. Befus, Chad R. University of Lethbridge. Faculty of Arts and Science 2011-09-06T18:21:42Z 2011-09-06T18:21:42Z 2010
dc.description viii, 94 leaves : ill. ; 29 cm en_US
dc.description.abstract Segmentation is an indispensable step in the field of Music Information Retrieval (MIR). Segmentation refers to the splitting of a music piece into significant sections. Classically there has been a great deal of attention focused on various issues of segmentation, such as: perceptual segmentation vs. computational segmentation, segmentation evaluations, segmentation algorithms, etc. In this thesis, we conduct a series of perceptual experiments which challenge several of the traditional assumptions with respect to segmentation. Identifying some deficiencies in the current segmentation evaluation methods, we present a novel standardized evaluation approach which considers segmentation as a supportive step towards feature extraction in the MIR process. Furthermore, we propose a simple but effective segmentation algorithm and evaluate it utilizing our evaluation approach. 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 Melodic analysis -- Data processing en_US
dc.subject Musical analysis -- Data processing en_US
dc.subject Music and technology en_US
dc.subject Signal processing -- Digital techniques en_US
dc.subject Pattern recognition systems en_US
dc.subject Dissertations, Academic en_US
dc.title Design and evaluation of dynamic feature-based segmentation on music 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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