Title :
A Comparison of Timbral and Harmonic Music Segmentation Algorithms
Author :
Levy, M. ; Noland, K. ; Sandler, Mark
Author_Institution :
Centre for Digital Music, London Univ., UK
Abstract :
Four music segmentation algorithms are presented, one based on purely timbral features, one on purely harmonic features, and two on different combinations of features. They are compared against each other and against human annotations of two albums by The Beatles. Example segmentations are given together with a quantitative measure of boundary accuracy. No algorithm is found to be clearly superior, although examples suggest that the combined algorithms can offer improved boundary detection.
Keywords :
acoustic signal processing; music; boundary detection; harmonic music segmentation; timbral music segmentation; Clustering algorithms; Data mining; Hidden Markov models; Histograms; Humans; MPEG 7 Standard; Multiple signal classification; Music information retrieval; Testing; Timbre; boundary evaluation; information retrieval; music; segmentation;
Conference_Titel :
Acoustics, Speech and Signal Processing, 2007. ICASSP 2007. IEEE International Conference on
Conference_Location :
Honolulu, HI
Print_ISBN :
1-4244-0727-3
DOI :
10.1109/ICASSP.2007.367349