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	Cross-Similarity Measurement of Music Sections: A Framework for Large-scale Cover Song Identification
	Cai, Kang ; Yang, Deshun ; Chen, Xiaoou
	2017
关键词	cross-similarity measurement music structure segmentation large-scale cover song identification
英文摘要	For large-scale cover song identification, most previous works take a single feature vector as the representation of a song. Although this approach ensures structure invariance, it may cause overcorrection since it totally neglects the structure feature of the song. To address this problem, we put forward a novel framework for large-scale cover song identification based on music structure segmentation, aiming at matching the irrelevant sections and ignoring the irrelevant ones. In our implementation, we apply the average and weighted average methods to integrating similarities of section pairs. We evaluate the proposed framework based on three representative previous methods, including 2D Fourier magnitude coefficients, chord profiles, and cognition-inspired descriptors. The experimental results show that the all the three methods in our framework significantly outperform those in their original works.; CPCI-S(ISTP); 151-158; 63
语种	英语
出处	12th International Conference on Intelligent Information Hiding and Multimedia Signal Processing (IIH-MSP)
DOI标识	10.1007/978-3-319-50209-0_19
内容类型	其他
源URL	[http://ir.pku.edu.cn/handle/20.500.11897/469914]
专题	信息科学技术学院
推荐引用方式 GB/T 7714	Cai, Kang,Yang, Deshun,Chen, Xiaoou. Cross-Similarity Measurement of Music Sections: A Framework for Large-scale Cover Song Identification. 2017-01-01.

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