Overlapping Animal Sound Classification Using Sparse Representation

Abstract

In this paper, a new method to classify the animal sound signals that are overlapped in time-frequency domain based on sparse representation is proposed. In order to obtain a discriminant sparse representation of overlapped animal sound signals, a novel dictionary atom discriminant factor is introduced. Then the proposed method generates a representation that contains crucial signal discriminant information for classification and the sparsity for sparsest representation. The experimental results show that the proposed method has a much superior performance than the conventional sparse representation based classification method for classifying the overlapped animal sound signals.