Classification of Dance Music by Periodicity Patterns

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dc.contributor.authorSimon Dixonen_US
dc.contributor.authorElias Pampalken_US
dc.contributor.authorGerhard Widmeren_US
dc.contributor.editorHolger H. Hoosen_US
dc.contributor.editorDavid Bainbridgeen_US
dc.date.accessioned2004-10-21T04:26:29Z
dc.date.available2004-10-21T04:26:29Z
dc.date.issued2003-10-26en_US
dc.description.abstractThis paper addresses the genre classification problem for a specific subset of music, standard and Latin ballroom dance music, using a classification method based only on timing information. We compare two methods of extracting periodicities from audio recordings in order to find the metrical hierarchy and timing patterns by which the style of the music can be recognised: the first method performs onset detection and clustering of inter-onset intervals; the second uses autocorrelation on the amplitude envelopes of band-limited versions of the signal as its method of periodicity detection. The relationships between periodicities are then used to find the metrical hierarchy and to estimate the tempo at the beat and measure levels of the hierarchy. The periodicities are then interpreted as musical note values, and the estimated tempo, meter and the distribution of periodicities are used to predict the style of music using a simple set of rules. The methods are evaluated with a test set of standard and Latin dance music, for which the style and tempo are given on the CD cover, providing a "ground truth" by which the automatic classification can be measured.en_US
dc.format.extent308114 bytes
dc.format.mimetypeapplication/pdf
dc.identifier.isbn0-9746194-0-Xen_US
dc.identifier.urihttp://jhir.library.jhu.edu/handle/1774.2/23
dc.language.isoen_US
dc.publisherJohns Hopkins Universityen_US
dc.subjectAudioen_US
dc.subjectIR Systems and Algorithmsen_US
dc.titleClassification of Dance Music by Periodicity Patternsen_US
dc.typeArticleen_US
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