Playing in unison in the random forest

Authors:
Alicja A. Wieczorkowska;Miron B. Kursa;Elż/bieta Kubera;Rados$#322/aw Rudnicki;Witold R. Rudnicki
Affiliations:
Polish-Japanese Institute of Information Technology, Warsaw, Poland;Interdisciplinary Centre for Mathematical and Computational Modelling, University of Warsaw, Warsaw, Poland;University of Life Sciences in Lublin, Lublin, Poland;Department of Music, The University of York, Heslington, York, UK;Interdisciplinary Centre for Mathematical and Computational Modelling, University of Warsaw, Warsaw, Poland
Venue:
SIIS'11 Proceedings of the 2011 international conference on Security and Intelligent Information Systems
Year:
2011

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Abstract

In this paper, we deal with the difficult problem of automatic identification of multiple instruments playing sounds of the same pitch, i.e. in unison. Random forests have been selected to be used as a classifier. Training data represent isolated sounds of selected instruments which originate from three commonly used repositories, namely McGill University Master Samples, The University of IOWA Musical Instrument Samples, and RWC. Testing data represent audio records especially prepared by one of the authors for research purposes, and next carefully labeled. The experiments on identification of instruments in a frame-by-frame manner and the obtained results are presented and discussed.