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In this paper, a novel deep neural network (DNN) architecture is proposed to generate the speech features of both the target speaker and interferer for speech separation without using any prior information about the interfering speaker. DNN is adopted here to directly model the highly nonlinear relationship between speech features of the mixed signals and the two competing speakers. Experimental results...
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