DocumentCode :
3638070
Title :
Automatic Music Genre Classification Using Bass Lines
Author :
Umut Simsekli
Author_Institution :
Dept. of Comput. Eng., Bogazici Univ., Istanbul, Turkey
fYear :
2010
Firstpage :
4137
Lastpage :
4140
Abstract :
A bass line is an instrumental melody that encapsulates both rhythmic, melodic, and harmonic features and arguably contains sufficient information for accurate genre classification. In this paper a bass line based automatic music genre classification system is described. "Melodic Interval Histograms" are used as features and k-nearest neighbor classifiers are utilized and compared with SVMs on a small size standard MIDI database. Apart from standard distance metrics for k-nearest neighbor (Euclidean, symmetric Kullback-Leibler, earth mover´s, normalized compression distances) we propose a novel distance metric, perceptually weighted Euclidean distance (PWED). The maximum classification accuracy (84%) is obtained with k-nearest neighbor classifiers and the added utility of the novel metric is illustrated in our experiments.
Keywords :
"Histograms","Accuracy","Complexity theory","Euclidean distance","Kernel","Instruments"
Publisher :
ieee
Conference_Titel :
Pattern Recognition (ICPR), 2010 20th International Conference on
ISSN :
1051-4651
Print_ISBN :
978-1-4244-7542-1
Type :
conf
DOI :
10.1109/ICPR.2010.1006
Filename :
5597729
Link To Document :
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