Abstract
In this paper, we address the problem of automatic identification of instruments in audio records, in a frame-by-frame manner. Random forests have been chosen as a classifier. Training data represent 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, as well as from recordings by one of the authors. Testing data represent audio records especially prepared for research purposes, and then carefully labeled (annotated). The experiments on identification of instruments on frame-by-frame basis and the obtained results are presented and discussed in the paper.
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Kubera, E., Kursa, M.B., Rudnicki, W.R., Rudnicki, R., Wieczorkowska, A.A. (2011). All That Jazz in the Random Forest. In: Kryszkiewicz, M., Rybinski, H., Skowron, A., Raś, Z.W. (eds) Foundations of Intelligent Systems. ISMIS 2011. Lecture Notes in Computer Science(), vol 6804. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21916-0_58
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DOI: https://doi.org/10.1007/978-3-642-21916-0_58
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