Comparison of time series similarity measures for plagiarism detection in music

Music is present everywhere around us. It is present in car rides, hotels, homes, television shows, movies, etc. With a huge demand of songs for bands, movies, etc., writers and singers are pressurised to produce new songs, but face the challenge of ensuring that they are not copying an already existing song in any way. With the growing music industry, cases of plagiarism have become a critical concern for musicians. An enormous number of musical tracks are released every year. So, there arises a need of a reliable and easy way to search through the huge database of songs that match the query song. In this paper, we have implemented the five similarity measure algorithms in MATLAB and did the comparative analysis of using them to distinguish among three sets of songs: a pair of plagiarized songs, a pair of same song with different lengths, and a random pair of songs to find the best fit algorithm for plagiarism detection.