Inter genre similarity modeling for automatic music genre classification

被引:0
|
作者
Bagci, Ulas [1 ]
Erzin, Engin [1 ]
机构
[1] Koc Univ, Muhendislik Fak, TR-34450 Istanbul, Turkey
关键词
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暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Two important problems of the automatic music genre classification are feature extraction and classifier design. This paper investigates inter-genre similarity modeling (IGS) to improve the automatic music genre classification performance. Inter-genre similarity information is extracted over the mis-classified feature population. Once the inter-genre similarity is modeled, elimination of the inter-genre similarity reduces the inter-genre confusion and improves the identification rates. Inter-genre similarity modeling is further improved with iterative IGS modeling and score modeling for IGS elimination. Experimental results with promising classification improvements are provided.
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页码:639 / +
页数:2
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