Region-Constrained Binaural Near-field Adaptive Beamforming Algorithm

To solve the problem that the traditional binaural near-field beamformer is too sensitive to the azimuth estimation error and the position disturbance of the desired sound source, a region-constrained binaural near-field adaptive beamforming algorithm is proposed, which applies the singular value decomposition method on a matrix composed of the steering vectors corresponding to the desired signal and several discrete points in its nearby area, and then obtains the enhanced speech signal by minimizing the output signal power subject to some constraints on these main eigenvectors. Experimental results show that the proposed algorithm can suppress far-filed co-directional interference effectively and is more robust than the traditional binaural near-field beamforming algorithms. Additionally, objective evaluation results show that the noise reduction performance and speech quality improvement of the proposed algorithm are superior to the competing algorithms.