Musical Instruments in Random Forest

Authors:
Miron Kursa;Witold Rudnicki;Alicja Wieczorkowska;Elżbieta Kubera;Agnieszka Kubik-Komar
Affiliations:
Interdisciplinary Centre for Mathematical and Computational Modelling (ICM), University of Warsaw, Warsaw, Poland 02-106;Interdisciplinary Centre for Mathematical and Computational Modelling (ICM), University of Warsaw, Warsaw, Poland 02-106;Polish-Japanese Institute of Information Technology, Warsaw, Poland 02-008;University of Life Sciences in Lublin, Lublin, Poland 20-950;University of Life Sciences in Lublin, Lublin, Poland 20-950
Venue:
ISMIS '09 Proceedings of the 18th International Symposium on Foundations of Intelligent Systems
Year:
2009

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Abstract

This paper describes automatic classification of predominant musical instrument in sound mixes, using random forests as classifiers. The description of sound parameterization applied and methodology of random forest classification are given in the paper. Additionally, the significance of sound parameters used as conditional attributes is investigated. The results show that almost all sound attributes are informative, and random forest technique yields much higher classification results than support vector machines, used in previous research on these data.