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. / viii, 94 leaves : ill. ; 29 cm
| Identifer | oai:union.ndltd.org:LACETR/oai:collectionscanada.gc.ca:ALU.w.uleth.ca/dspace#10133/2531 |
| Date | January 2010 |
| Creators | Befus, Chad R, University of Lethbridge. Faculty of Arts and Science |
| Contributors | Zhang, John Z |
| Publisher | Lethbridge, Alta. : University of Lethbridge, Dept. of Mathematics and Computer Science, c2010, Arts and Science, Department of Mathematics and Computer Science |
| Source Sets | Library and Archives Canada ETDs Repository / Centre d'archives des thèses électroniques de Bibliothèque et Archives Canada |
| Language | en_US |
| Detected Language | English |
| Type | Thesis |
| Relation | Thesis (University of Lethbridge. Faculty of Arts and Science) |
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