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.
Please Note: This is an On Demand product, delivery may take up to 11 working days after payment has been received.
Table of Contents
1. Introduction2. Fundamentals of Deep Learning
3. Voice Activity Detection
4. Single-Channel Speech Enhancement
5. Multi-Channel Speech Enhancement
6. Multi-Speaker Speech Separation
7. Speaker Recognition
8. Speech Recognition
Authors
Xiao-Lei Zhang Northwestern Polytechnical University, Xi'an, China.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.
