Speech Enhancement Based on Binaural Sound Source Localization and Cosh Measure Wiener Filtering

The existing speech enhancement algorithm has shown poor performance under low Signal Noise Ratios (SNRs). To resolve this problem, a speech enhancement algorithm based on binaural sound source localization and cosh measure filtering is proposed. Firstly, the algorithm uses a sound source localization algorithm based on head correlation functions and two-level deep learning to extract the spatial information of the binaural sound source and determine the spatial position of the sound source. The beamforming method is then used to remove the noises in different directions from the speech. Finally, the Wiener filtering of cosh measure based on logarithmic relation is used to remove the noise in the same direction as the speech to achieve speech enhancement. Experiments show that the proposed algorithm has better robustness and denoising ability than the contrast algorithms.