Review of Monaural Speech Enhancement Based on Deep Neural Networks

Speech enhancement tries to separate speech from noise and aims to improve the quality and intelligibility of speech. In the past several decades, many types of speech enhancement methods have been proposed. However, these methods cannot always achieve the best performance for non-stationary noise because they do not make best use of prior information of speech and noise. In recent years, with the advance of deep learning, the deep neural network (DNN) has become a mainstream strategy to conduct speech enhancement, and is playing important role in improving speech quality and increasing intelligibility. Based on the structure the DNN, the DNN-based monaural speech enhancement methods are reviewed in this paper. First, the background of speech enhancement is introduced. Next, four different types of the DNN used for conducting speech enhancement are carefully described. Finally, some comments of speech enhancement for future work and conclusions are given.