Abstract
An application of RS knowledge discovery methods for automatic classification of musical instrument sounds is presented. Also, we provide basic information on acoustics of musical instruments. Since the digital record of sound contains a huge amount of data, the redundancy in the data is fixed via parameterization. The parameters extracted from sounds of musical instrument are discussed. We use quantization as a preprocessing for knowledge discovery to limit the number of parameter values. Next we show exemplary methods of quantization of parameter values. Finally, experiments concerning audio signal classification using rough set approach are presented and the results are discussed.KeywordsMusical InstrumentAutomatic ClassificationSoft Computing TechniqueString InstrumentSound ParameterThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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