Abstract
The goal of the presented research was to recognize musical instruments in sound mixes for various levels of accompanying sounds, on the basis of a limited number of sound parameters. Discriminant analysis was used for this purpose. Reduction of the initial large set of sound parameters was performed by means of PCA (principal components analysis), and the factors found using PCA were utilized as input data for discriminant analysis. The results of the discriminant analysis allowed us to assess the accuracy of linear classification on the basis the factors found, and conclude about sound parameters of the highest discriminant power.
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Wieczorkowska, A., Kubik-Komar, A. (2009). Application of Discriminant Analysis to Distinction of Musical Instruments on the Basis of Selected Sound Parameters. In: Cyran, K.A., Kozielski, S., Peters, J.F., Stańczyk, U., Wakulicz-Deja, A. (eds) Man-Machine Interactions. Advances in Intelligent and Soft Computing, vol 59. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-00563-3_43
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DOI: https://doi.org/10.1007/978-3-642-00563-3_43
Publisher Name: Springer, Berlin, Heidelberg
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