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面向翻唱歌曲识别的相似度融合算法
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].医学教育探索,2016(6):845-850.
作者姓名:刘婷  陈宁
作者单位:华东理工大学信息科学与工程学院, 上海 200237,华东理工大学信息科学与工程学院, 上海 200237
基金项目:国家自然科学基金(61271349)
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。

关 键 词:相似度融合  节拍追踪  瞬时频率音级轮廓  和声音级轮廓  耳蜗音级轮廓  Qmax  翻唱歌曲识别
收稿时间:2015/12/24 0:00:00

Similarity Distance Fusion Algorithm in Cover Song Identification
LIU Ting and CHEN Ning.Similarity Distance Fusion Algorithm in Cover Song Identification[J].Researches in Medical Education,2016(6):845-850.
Authors:LIU Ting and CHEN Ning
Institution:School of Information Science and Engineering, East China University of Science and Technology, Shanghai 200237, China and School of Information Science and Engineering, East China University of Science and Technology, Shanghai 200237, China
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.
Keywords:similarity distance fusion  beat tracing  IF-PCP  HPCP  CPCP  Qmax  cover song identification
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