An efficient approach to extracting approximate repeating patterns in music databases

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Abstract

Pattern extraction from music strings is an important problem. The patterns extracted from music strings can be used as features for music retrieval or analysis. Previous works on music pattern extraction only focus on exact repeating patterns. However, music segments with minor differences may sound similar. The concept of the prototypical melody has therefore been proposed to represent these similar music segments. In musicology, the number of music segments that are similar to a prototypical melody implies the importance degree of the prototypical melody to the music work. In this paper, a novel approach is developed to extract all the prototypical melodies in a music work. Our approach considers each music segment as a candidate for the prototypical melody and uses the edit distance to determine the set of music segments that are similar to this candidate. A lower bounding mechanism, which estimates the number of similar music segments for each candidate and prunes the impossible candidates is designed to speed up the process. Experiments are performed on a real data set and the results show a significant improvement of our approach over the existing approaches in the average response time. © Springer-Verlag Berlin Heidelberg 2005.

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Liu, N. H., Wu, Y. H., & Chen, A. L. P. (2005). An efficient approach to extracting approximate repeating patterns in music databases. In Lecture Notes in Computer Science (Vol. 3453, pp. 240–252). Springer Verlag. https://doi.org/10.1007/11408079_23

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