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Music classification using high-level models

Title Music classification using high-level models
Publication Type Miscellaneous
Year of Publication 2010
Authors Wack, N. , Laurier C. , Meyers O. , Marxer R. , Bogdanov D. , Serrà J. , Gómez E. , & Herrera P.
Abstract We 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.
Notes Access to MIREX2010 results:
preprint/postprint document files/publications/WLB1.pdf