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Rhythmic similarity of music based on dynamic periodicity warping
2008 (English)In: Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing. ICASSP, IEEE conference proceedings, 2008, 2217-2220 p.Conference paper (Refereed)
Abstract [en]

This paper introduces a new way to measure rhythmic similarity between two musical pieces using periodicity spectra. In order to detect similarity for pieces of different tempi, the linearity of the warping path between their spectra serves as a measure of their rhythmic similarity. Using a modified kNN classification approach on two datasets, the proposed measure provides comparable classification accuracy (82.1%) to the best of widely used measures (85.5%) for the first dataset; For the second dataset, which is characterized by a large variance of tempi, the proposed measure outperforms all reference measures, reaching an accuracy of 69.0%, while the best of the other measures reaches 53.8%. Moreover, the presented technique works fully automatically, and no information regarding tempo is needed.

Place, publisher, year, edition, pages
IEEE conference proceedings, 2008. 2217-2220 p.
Keyword [en]
rhythm; similarity; music; information retrieval
National Category
Media Engineering
Identifiers
URN: urn:nbn:se:kth:diva-193762DOI: 10.1109/ICASSP.2008.4518085ISI: 000257456701216ScopusID: 2-s2.0-51449098969OAI: oai:DiVA.org:kth-193762DiVA: diva2:1040360
Conference
IEEE International Conference on Acoustics, Speech, and Signal Processing. ICASSP
Note

QC 20161031

Available from: 2016-10-27 Created: 2016-10-10 Last updated: 2016-10-31Bibliographically approved

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