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    刘婷, 陈宁. 面向翻唱歌曲识别的相似度融合算法[J]. 华东理工大学学报(自然科学版), 2016, (6): 845-850. DOI: 10.14135/j.cnki.1006-3080.2016.06.015
    引用本文: 刘婷, 陈宁. 面向翻唱歌曲识别的相似度融合算法[J]. 华东理工大学学报(自然科学版), 2016, (6): 845-850. DOI: 10.14135/j.cnki.1006-3080.2016.06.015
    LIU Ting, CHEN Ning. Similarity Distance Fusion Algorithm in Cover Song Identification[J]. Journal of East China University of Science and Technology, 2016, (6): 845-850. DOI: 10.14135/j.cnki.1006-3080.2016.06.015
    Citation: LIU Ting, CHEN Ning. Similarity Distance Fusion Algorithm in Cover Song Identification[J]. Journal of East China University of Science and Technology, 2016, (6): 845-850. DOI: 10.14135/j.cnki.1006-3080.2016.06.015

    面向翻唱歌曲识别的相似度融合算法

    Similarity Distance Fusion Algorithm in Cover Song Identification

    • 摘要: 提出了一种面向翻唱歌曲识别的相似度融合算法。该算法将基于乐理特征的相似度和基于人耳感知特性的相似度融合,通过把基于节拍跟踪和瞬时频率音级轮廓(IF-PCP)的最大互相关相似度、基于和声音级轮廓(HPCP)的Qmax相似度、基于耳蜗音级轮廓(CPCP)的Qmax相似度映射到同一个多维空间,并计算其几何距离来进行相似度融合。该算法使得IF-PCP特征的节拍速度不变性、HPCP特征的和声优势、CPCP特征的人耳感知特性有效融合。为了验证算法的有效性,采用包含212首不同歌曲共502个版本的数据库作为测试对象,以平均正确率均值和TOP-N作为测试指标对算法性能进行测试。测试结果表明,与基于单一相似度算法相比,该融合算法可提高翻唱歌曲识别准确率。

       

      Abstract: This paper proposes a new similarity distance fusion algorithm that fuses the similarity distance of music theory feature and auditory perceptual feature.In the proposed algorithm,three similarity distances,IF-PCP based on beat tracing with maximum cross-correlation measure,HPCP with Qmax measure,and CPCP with Qmax measure,are projected in a multi-dimensional space and then the geometric distance as the fusion similarity distance is computed.This algorithm can effectively integrate the beat speed invariance of IF-PCP,the harmonic advantage of HPCP,and the auditory perceptual of CPCP.An experiment on a database with 502 versions of 212 different songs is made in this work.By mean of MAP and TOP-N as the performance indicator of the cover song identification,it is shown that the proposed algorithm in this paper can improve the precision of cover song identification greatly.

       

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