Guest Editorial: Special Issue on Advances in Deep Learning Based Speech Processing Xiao-Lei Zhanga, Lei Xieb, Eric Fosler-Lussierc, Emmanuel Vincentd aSchool of Marine Science and Technology, Northwestern Polytechnical University, Xi’an, Shaanxi 710072, China. bAudio, Speech and Language Processing Group (ASLP@NPU), School of Computer Science, Northwestern Polytechnical University, Xi’an, Shaanxi 710072, China. cDepartment of Computer Science and Engineering, The Ohio State University, Columbus, OH 43210, USA. dUniversité de Lorraine, CNRS, Inria, LORIA, F-54000, Nancy, France. Deep learning has triggered a big revolution on speech pro-cessing. The revolution started from the successful application of deep neural networks to automatic speech recognition, and was quickly spread to other topics of speech processing, in-cluding speech analysis, speech enhancement and separation, speaker and language recognition, speech synthesis, and spoken language understanding. Such tremendous success is achieved by the long-term evolution of neural network technologies as well as the big explosion of speech data and fast development of computing power.