Lin Zhou1,*, Kangyu Ma1, Lijie Wang1, Ying Chen1,2, Yibin Tang3
CMC-Computers, Materials & Continua, Vol.60, No.2, pp. 545-557, 2019, DOI:10.32604/cmc.2019.05969
Abstract Binaural sound source localization (BSSL) in low signal-to-noise ratio (SNR) and high reverberation environment is still a challenging task. In this paper, a novel BSSL algorithm is proposed by introducing convolutional neural network (CNN). The proposed algorithm first extracts the spatial feature of each sub-band from binaural sound signal, and then combines the features of all sub-bands within one frame to assemble a two-dimensional feature matrix as a grey image. To fully exploit the advantage of the CNN in extracting high-level features from the grey image, the spatial feature matrix of each frame is used More >
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