DCCRN: Deep Complex Convolution Recurrent Network for Phase-Aware Speech Enhancement

Speech enhancement has benefited from the success of deep learning in terms of intelligibility and perceptual quality.Conventional time-frequency (TF) domain methods focus on predicting TF-masks or speech spectrum, via a naive convolution neural network (CNN) or recurrent neural network (RNN).Some recent studies use complex-valued spectrogram as a training target but train in a real-valued network, predicting the magnitude and phase component or real and imaginary part, respectively.Particularly, convolution recurrent network (CRN) integrates a convolutional encoder-decoder (CED) structure and long short-term memory (LSTM), which has been proven to be helpful for complex targets.In order to train the complex…