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.
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Wieczorkowska, A.A., Kursa, M.B., Kubera, E., Rudnicki, R., Rudnicki, W.R. (2012). Playing in Unison in the Random Forest. In: Bouvry, P., Kłopotek, M.A., Leprévost, F., Marciniak, M., Mykowiecka, A., Rybiński, H. (eds) Security and Intelligent Information Systems. SIIS 2011. Lecture Notes in Computer Science, vol 7053. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25261-7_18
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DOI: https://doi.org/10.1007/978-3-642-25261-7_18
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