2026-09-21T07:34:13Z https://www.ideals.illinois.edu/oai-pmh

oai:www.ideals.illinois.edu:2142/95426 2023-07-11 col_2142_5131 col_2142_8888 com_2142_5130 com_2142_8887 com_2142_234

Hasegawa Johnson, Mark Lai, Yuhui 2017-03-01T15:49:36Z 2017-03-01T15:49:36Z 2016-12-09 2016-12 In this thesis, we evaluate content-based acoustic features for musical genre classification. Effectiveness of various acoustic features are compared using a k-nearest neighbor (KNN) classifier. By utilizing the combinations of acoustic features, an average classification accuracy of $89\%$ for GTZAN database is achieved, which is comparable to prior work. A statistical test, McNemar's test, is applied to support the idea that musical genre is intrinsically related to content-based acoustic features. Especially for some genres, we are able to identify the particular associated acoustic property. In addition, by comparing our KNN results to a psychoacoustic listening experiment, we associate various human perceptual dimensions with low-level acoustic features. Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2017-02-28 without embargo terms The student, Yuhui Lai, accepted the attached license on 2016-12-09 at 03:00. The student, Yuhui Lai, submitted this Thesis for approval on 2016-12-09 at 03:08. This Thesis was approved for publication on 2016-12-09 at 09:45. DSpace SAF Submission Ingestion Package generated from Vireo submission #10498 on 2017-02-28 at 15:04:18 Made available in DSpace on 2017-03-01T15:49:36Z (GMT). No. of bitstreams: 2 LAI-THESIS-2016.pdf: 1573391 bytes, checksum: d0dee8adbdc29548a5657e88e9961e7b (MD5) LICENSE.txt: 4206 bytes, checksum: 01e42718e0c24425cd49ef7f80370d48 (MD5) Previous issue date: 2016-12-09 application/pdf http://hdl.handle.net/2142/95426 en Copyright 2016 Yuhui Lai Music genre classification k-nearest neighbor (KNN) Content-based acoustic feature Evaluation of content-based acoustic features for musical genre classification text text Electrical & Computer Eng Electrical & Computer Engr University of Illinois at Urbana-Champaign Thesis M.S.