Similarity Distance Fusion Algorithm in Cover Song Identification

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 Q_max measure,and CPCP with Q_max 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.