Extracting Theme Melodies by Using a Graphical Clustering Algorithm for Content-Based Music Information Retrieval

We proposed the mechanism of extracting theme melodies from a song by using a graphical clustering algorithm. In the proposed mechanism, a song is split into the set of motifs each of which is the minimum meaningful unit. Then the system clusters the motifs into groups based on the similarity values calculated between all pairs of motifs so that each cluster has higher similarity values between them than others. From each clusters, the system selects a theme melody based on the positions of the motif within a song and the maximum summation of similarity values of edges adjacent to the motif node in each cluster. As the experimental results, we showed an example in which we describe how the theme melodies of a song can be extracted by using the proposed algorithm.

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