Automatic Detection of Song Changes in Music Mixes Using Stochastic Models

Plötz T, Fink GA, Husemann P, Kanies S, Lienemann K, Marschall T, Martin M, Schillingmann L, Steinrücken M, Sudek H (2006)
In: Proc. ICPR 2006. International Association for Pattern Recognition (Ed); , 3. Los Alamitos, Calif. : IEEE: 665-668.

Konferenzbeitrag | Veröffentlicht | Englisch
 
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Autor*in
Plötz, Thomas; Fink, Gernot A.; Husemann, PeterUniBi; Kanies, Sven; Lienemann, Kai; Marschall, TobiasUniBi; Martin, MarcelUniBi; Schillingmann, LarsUniBi; Steinrücken, Matthias; Sudek, HennerUniBi
herausgebende Körperschaft
International Association for Pattern Recognition
Abstract / Bemerkung
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.
Erscheinungsjahr
2006
Titel des Konferenzbandes
Proc. ICPR 2006
Band
3
Seite(n)
665-668
ISBN
0769525210
Page URI
https://pub.uni-bielefeld.de/record/1893905

Zitieren

Plötz T, Fink GA, Husemann P, et al. Automatic Detection of Song Changes in Music Mixes Using Stochastic Models. In: International Association for Pattern Recognition, ed. Proc. ICPR 2006. Vol 3. Los Alamitos, Calif. : IEEE; 2006: 665-668.
Plötz, T., Fink, G. A., Husemann, P., Kanies, S., Lienemann, K., Marschall, T., Martin, M., et al. (2006). Automatic Detection of Song Changes in Music Mixes Using Stochastic Models. In International Association for Pattern Recognition (Ed.), Proc. ICPR 2006 (Vol. 3, pp. 665-668). Los Alamitos, Calif. : IEEE. https://doi.org/10.1109/icpr.2006.297
Plötz, T., Fink, G. A., Husemann, P., Kanies, S., Lienemann, K., Marschall, T., Martin, M., Schillingmann, L., Steinrücken, M., and Sudek, H. (2006). “Automatic Detection of Song Changes in Music Mixes Using Stochastic Models” in Proc. ICPR 2006, International Association for Pattern Recognition ed., vol. 3, (Los Alamitos, Calif. : IEEE), 665-668.
Plötz, T., et al., 2006. Automatic Detection of Song Changes in Music Mixes Using Stochastic Models. In International Association for Pattern Recognition, ed. Proc. ICPR 2006. no.3 Los Alamitos, Calif. : IEEE, pp. 665-668.
T. Plötz, et al., “Automatic Detection of Song Changes in Music Mixes Using Stochastic Models”, Proc. ICPR 2006, International Association for Pattern Recognition, ed., vol. 3, Los Alamitos, Calif. : IEEE, 2006, pp.665-668.
Plötz, T., Fink, G.A., Husemann, P., Kanies, S., Lienemann, K., Marschall, T., Martin, M., Schillingmann, L., Steinrücken, M., Sudek, H.: Automatic Detection of Song Changes in Music Mixes Using Stochastic Models. In: International Association for Pattern Recognition (ed.) Proc. ICPR 2006. 3, p. 665-668. IEEE, Los Alamitos, Calif. (2006).
Plötz, Thomas, Fink, Gernot A., Husemann, Peter, Kanies, Sven, Lienemann, Kai, Marschall, Tobias, Martin, Marcel, Schillingmann, Lars, Steinrücken, Matthias, and Sudek, Henner. “Automatic Detection of Song Changes in Music Mixes Using Stochastic Models”. Proc. ICPR 2006. Ed. International Association for Pattern Recognition. Los Alamitos, Calif. : IEEE, 2006.Vol. 3. 665-668.

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