A study of the automatic classification of musical instrument sounds is presented. For this purpose a database of musical instrument sound parameters was built which consists of musical instrument recordings and their parametric representations. The parameterization process was conceived and performed in order to find significant musical instrument sound features and to remove redundancy from the musical signal. Classification experiments of musical instrument sounds were performed with neural networks allowing a discussion of the efficiency of the feature extraction process and its limitations. Conclusions and remarks concerning further development of this study and its relation to the current MPEG-7 standardization process are included.
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