TU Dortmund Department of Computer Science LS XII Pattern Recognition GroupPublications → Publication Details

Automatic Detection of Song Changes in Music Mixes Using Stochastic Models

Thomas Pl{\"o}tz AND Gernot A.\ Fink AND Peter Husemann AND Sven Kanies AND Kai Lienemann AND Tobias Marschall AND Marcel Martin and Lars Schillingmann AND Matthias Steinr{\"u}cken AND Henner Sudek
Proc. Int. Conf. on Pattern Recognition, pages 665-668, 2006.

The annotation of song changes in music mixes created by DJs or radio stations for direct access in digital recordings is, usually, a very tedious work. In order to support this process we developed an automatic song change detection method which can be used for arbitrary music mixes. Stochastic models are applied to music data aiming at their segmentation with respect to automatically obtained abstract generic acoustic units. The local analysis of these stochastic music models provides hypotheses for song changes. Results of an experimental evaluation processing music mix data demonstrate the effectiveness of our method for supporting the annotation with respect to song changes.

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