Robust binaural speech separation in adverse conditions based on deep neural network with modified spatial features and training target

Publication date: Available online 20 February 2019Source: Speech CommunicationAuthor(s): Paria Dadvar, Masoud GeravanchizadehAbstractIn this paper, a robust binaural speech separation system based on deep neural network (DNN) is introduced. The proposed system has three main processing stages. In the spectral processing stage, the multiresolution cochleagram (MRCG) feature is extracted from the beamformed signal. In the spatial processing stage, a novel reliable spatial feature of smITD+smILD is obtained by soft missing data masking of binaural cues. In the final stage, a deep neural network takes the combined spectral and spatial features and estimates a newly defined ideal ratio mask (IRM) designed for noisy and reverberant conditions. The performance of the proposed system is evaluated...

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