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Proceedings Paper

Musical structure analysis using similarity matrix and dynamic programming
Author(s): Yu Shiu; Hong Jeong; C.-C. Jay Kuo
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Paper Abstract

Automatic music segmentation and structure analysis from audio waveforms based on a three-level hierarchy is examined in this research, where the three-level hierarchy includes notes, measures and parts. The pitch class profile (PCP) feature is first extracted at the note level. Then, a similarity matrix is constructed at the measure level, where a dynamic time warping (DTW) technique is used to enhance the similarity computation by taking the temporal distortion of similar audio segments into account. By processing the similarity matrix, we can obtain a coarse-grain music segmentation result. Finally, dynamic programming is applied to the coarse-grain segments so that a song can be decomposed into several major parts such as intro, verse, chorus, bridge and outro. The performance of the proposed music structure analysis system is demonstrated for pop and rock music.

Paper Details

Date Published: 24 October 2005
PDF: 12 pages
Proc. SPIE 6015, Multimedia Systems and Applications VIII, 601516 (24 October 2005); doi: 10.1117/12.633792
Show Author Affiliations
Yu Shiu, Univ. of Southern California (United States)
Hong Jeong, Pohang Institute of Technology (South Korea)
C.-C. Jay Kuo, Univ. of Southern California (United States)


Published in SPIE Proceedings Vol. 6015:
Multimedia Systems and Applications VIII
Anthony Vetro; Chang Wen Chen; C.-C. J. Kuo; Tong Zhang; Qi Tian; John R. Smith, Editor(s)

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