Dynamic texture models of music
Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review
Author(s)
Detail(s)
Original language | English |
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Title of host publication | ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings |
Pages | 1589-1592 |
Publication status | Published - 2009 |
Externally published | Yes |
Publication series
Name | |
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ISSN (Print) | 1520-6149 |
Conference
Title | 2009 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2009 |
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Place | Taiwan |
City | Taipei |
Period | 19 - 24 April 2009 |
Link(s)
Abstract
In this paper, we consider representing a musical signal as a dynamic texture, a model for both the timbral and rhythmical qualities of sound. We apply the new representation to the task of automatic song segmentation. In particular, we cluster sequences of audio feature-vectors, extracted from the song, using a dynamic texture mixture model (DTM). We show that the DTM model can both detect transition boundaries and accurately cluster coherent segments. The similarities between the dynamic textures which define these segments are based on both timbral and rhythmic qualities of the music, indicating that the DTM model simultaneously captures two of the important aspects required for automatic music analysis. ©2009 IEEE.
Research Area(s)
- Automatic segmentation, Dynamic texture model, Music modeling, Music similarity
Citation Format(s)
Dynamic texture models of music. / Barrington, Luke; Chan, Antoni B.; Lanckriet, Gert.
ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings. 2009. p. 1589-1592.
ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings. 2009. p. 1589-1592.
Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review