Music classification using high-level models

TitleMusic classification using high-level models
Publication TypeMiscellaneous
Year of Publication2010
AuthorsWack, N., Laurier C., Meyers O., Marxer R., Bogdanov D., Serrà J., Gómez E., & Herrera P.
AbstractWe report here about our submissions to different music classification tasks for the MIREX 2010 evaluations. These submissions are similar to the ones sent at MIREX 2009 (see [1]), if we look at the classifiers and the main audio features. However we added high-level features (or semantic features), based on Support Vector Machine models of curated databases of different kind. We submitted two different algorithms evaluated on Mood, Genre and Artists classification. One of them is a classification algorithm using a weighted sum of Support Vector Machines. The other one is based on distances (Euclidean in a reduced space using RCA and Kullback Leibler on Mel Frequency Cepstrum Coefficients), together with K-NN.
NotesAccess to MIREX2010 results: http://www.music-ir.org/mirex/wiki/2010:MIREX2010_Results
preprint/postprint documentfiles/publications/WLB1.pdf
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