Overview

Speech Signal Processing Based on Deep Learning in Complex Acoustic Environments provides a detailed discussion of deep learning-based robust speech processing and its applications. The book begins by looking at the basics of deep learning and common deep network models, followed by front-end algorithms for deep learning-based speech denoising, speech detection, single-channel speech enhancement multi-channel speech enhancement, multi-speaker speech separation, and the applications of deep learning-based speech denoising in speaker verification and speech recognition.

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Xiao-Lei Zhang received his Ph.D. degree with honors from Tsinghua University, China, in 2012. He was a postdoctoral researcher with the Department of Electronic Engineering at Tsinghua University from 2012 to 2014. He was a visiting scholar at The Ohio State University, USA, from 2013 to 2014 and a postdoctoral researcher with the Department of Computer Science and Engineering, The Ohio State University, from 2014 to 2016. Since 2016 he has been a full professor at the Northwestern Polytechnical University, Xi'an, China. His research interests are the topics in speech processing, machine learning, statistical signal processing, and artificial intelligence.

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