3D Speech Enhancement Algorithm for Two-Stage U-Net Beamforming Network

The noise in the 3D reverberation environment is detrimental to many downstream applications. The development of 3D speech enhancement technology suitable for realistic scenes has important theoretical significance and practical value in real life. This paper proposes a two-stage beamforming network for 3D speech enhancement in this scenario. The network consists of two consecutive multiple-input single-output U-Net beamforming networks. The first-level network mainly performs rough beamforming estimation on the 3D speech signal from the dual microphones, and filters out part of the signal noise. In order to further improve the estimation, the second-level network takes the characteristics of the rough estimated signal together with the characteristics of the omnidirectional channel information in the original signal as input, and performs the beamforming fine estimation to obtain a more accurate estimated signal and achieve the purpose of two-level enhancement. The dataset and experiments are based on the 3D speech enhancement task of the L3DAS22 challenges. The short-time objective intelligibility（STOI）obtained by this method on the blind test set is 0.925, and the word error rate（WER）reaches 13.6%, which is significantly better than the L3DAS21 3D speech enhancement challenge, the champion model in the competition（0.878 and 21.2%）. © 2023 Editorial Office Of Water Saving Irrigation. All rights reserved.