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    Sound Source Localization Based on SRP-PHAT Spatial Spectrum and Deep Neural Network

    Xiaoyan Zhao1, *, Shuwen Chen2, Lin Zhou3, Ying Chen3, 4

    CMC-Computers, Materials & Continua, Vol.64, No.1, pp. 253-271, 2020, DOI:10.32604/cmc.2020.09848

    Abstract Microphone array-based sound source localization (SSL) is a challenging task in adverse acoustic scenarios. To address this, a novel SSL algorithm based on deep neural network (DNN) using steered response power-phase transform (SRP-PHAT) spatial spectrum as input feature is presented in this paper. Since the SRP-PHAT spatial power spectrum contains spatial location information, it is adopted as the input feature for sound source localization. DNN is exploited to extract the efficient location information from SRP-PHAT spatial power spectrum due to its advantage on extracting high-level features. SRP-PHAT at each steering position within a frame is arranged into a vector, which… More >

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