Butterfly-like D-tree fusion strategy for real-time speech and music classification

Aimed at the problem of real-time speech and music discrimination, this paper proposes a frame-level classification method by using a novel “butterfly-like” fusion strategy based on decision tree (D-Tree).In our method, some homotypes of long-term features but in different time lengths are extracted to train each sub-classifier and make the fusion resultful. A testing experiment indicates our approach can achieve the desirable performance in reducing the misclassification and the imbalance of decision tree model. Meanwhile, superiorities in low overheads of computational complexity and memory resource make it competitive in practical applications.