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In this paper, a novel collective network of binary classifiers (CNBC) framework is presented for content-based audio classification. The topic has been studied in several publications before, but in many cases the number of different classification categories is quite limited and needed to be fixed a priori. We focus our efforts to increase both the classification accuracy and the number of classes,...
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