Multiexpert System for Automatic Music Genre Classification
نویسندگان
چکیده
Automatic classification of music pieces by genre is one of the crucial tasks in music categorization for intelligent navigation. In this work we present a multiExpert genre classification system based on acoustic, musical and timbre features. A novel rhythmic characteristic, 2D beat histogram is used as high-level musical feature. Timbre features are extracted by multiple-f0 detection algorithm. The multiExpert classifier is composed from three individual experts: acoustic expert, rhythmic expert and timbre analysis expert. Each of these experts produces a probability of a song to belong to a genre. The output of the multiExpert classifier is a neuron network combination of individual classifiers. It was shown in this work a 12% increase of classification rate for the multiExpert system in comparison to the best individual classifier.
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شناسایی خودکار سبک موسیقی
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