Detecting and Locating Plagiarism of Music Melodies by Path Exploration Over a Binary Mask


Mu-Syuan Sie, Cheng-Chin Chiang, Hsiu-Chun Yang and Yi-Le Liu, National Dong Hwa University, Taiwan


To the best of our knowledge, the issues of automatic detection of music plagiarism have never been addressed before. This paper presents the design of an Automatic Music Melody Plagiarism Detection (AMMPD) method to detect and locate the possible plagiarism in music melodies. The key contribution of the work is an algorithm proposed to address the challenging issues encountered in the AMMPD problem, including (1) the inexact matching of noisy and inaccurate pitches of music audio and (2) the fast detection and positioning of similar subsegments between suspicious music audio. The major novelty of the proposed method is that we address the above two issues in temporal domain by means of a novel path finding approach on a binarized 2-D bit mask in spatial domain. In fact, the proposed AMMPD method can not only identify the similar pieces inside two suspicious music melodies, but also retrieve music audio of similar melodies from a music database given a humming or singing query. Experiments have been conducted to assess the overall performance and examine the effects of various parameters introduced in the proposed method.


Music Melody Plagiarism, Music Melody Retrieval, Subsequence Matching, Warping Time Series Join

Full Text  Volume 7, Number 10