Embedding and Beamforming: All-neural Causal Beamformer for Multichannel Speech Enhancement
Andong Li, Wenzhe Liu, Chengshi Zheng, Xiaodong Li
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Standing upon the intersection of traditional beamformers and deep neural networks, we propose a causal neural beamformer paradigm called \emph{Embedding and Beamforming}, and two core modules are devised accordingly, namely EM and BM. For EM, instead of estimating spatial covariance matrix explicitly, the