Speech Enhancement

With the proliferation of mobile devices and hearing devices, including hearing aids and cochlear implants, there is a growing and pressing need to design algorithms that can improve speech intelligibility without sacrificing quality. Responding to this need, Speech Enhancement: Theory and Practice, Second Edition introduces readers to the basic problems of speech enhancement and the various algorithms proposed to solve these problems. Updated and expanded, this second edition of the bestselling textbook broadens its scope to include evaluation measures and enhancement algorithms aimed at improving speech intelligibility. Fundamentals, Algorithms, Evaluation, and Future Steps Organized into four parts, the book begins with a review of the fundamentals needed to understand and design better speech enhancement algorithms. The second part describes all the major enhancement algorithms and, because these require an estimate of the noise spectrum, also covers noise estimation algorithms. The third part of the book looks at the measures used to assess the performance, in terms of speech quality and intelligibility, of speech enhancement methods. It also evaluates and compares several of the algorithms. The fourth part presents binary mask algorithms for improving speech intelligibility under ideal conditions. In addition, it suggests steps that can be taken to realize the full potential of these algorithms under realistic conditions. What's New in This EditionUpdates in every chapter A new chapter on objective speech intelligibility measures A new chapter on algorithms for improving speech intelligibility Real-world noise recordings (on downloadable resources) MATLAB® code for the implementation of intelligibility measures (on downloadable resources) MATLAB and C/C++ code for the implementation of algorithms to improve speech intelligibility (on downloadable resources)
Valuable Insights from a Pioneer in Speech Enhancement Clear and concise, this book explores how human listeners compensate for acoustic noise in noisy environments. Written by a pioneer in speech enhancement and noise reduction in cochlear implants, it is an essential resource for anyone who wants to implement or incorporate the latest speech enhancement algorithms to improve the quality and intelligibility of speech degraded by noise. Includes downloadable resources with Code and Recordings The downloadable resources provide MATLAB implementations of representative speech enhancement algorithms as well as speech and noise databases for the evaluation of enhancement algorithms.

Philipos C. Loizou earned his bachelor's, master's, and doctorate degrees in electrical engineering from Arizona State University in Tempe. A pioneer in the field of speech enhancement and noise reduction in cochlear implants, Dr. Loizou was one of the first to develop specific enhancement algorithms that directly improve intelligibility. He was a postdoctoral fellow in the Department of Speech and Hearing Science at Arizona State University, an assistant professor at the University of Arkansas in Little Rock, and Cecil and Ida Green Professor in the Department of Electrical Engineering at the University of Texas at Dallas. Dr. Loizou was a fellow of the Acoustical Society of America. He was an associate editor of the International Journal of Audiology (2010-2012), IEEE Transactions on Biomedical Engineering (2009-2011), IEEE Transactions on Speech and Audio Processing (1999-2002), and IEEE Signal Processing Letters (2006-2009) and a member of the Speech Technical Committee (2008-2010) of the IEEE Signal Processing Society. He authored or coauthored numerous publications, including three textbooks. For more information, see Dr. Loizou's profile at the University of Texas at Dallas. Watch a video of Dr. Loizou talking about technology that would allow cochlear implant users to easily adjust settings on their hearing devices through a smartphone.

Introduction. Part I Fundamentals: Discrete-Time Signal Processing and Short-Time Fourier Analysis. Speech Production and Perception. Noise Compensation by Human Listeners. Part II Algorithms: Spectral-Subtractive Algorithms. Wiener Filtering. Statistical-Model-Based Methods. Subspace Algorithms. Noise-Estimation Algorithms. Part III Evaluation: Evaluating Performance of Speech Enhancement Algorithms. Objective Quality and Intelligibility Measures. Comparison of Speech Enhancement Algorithms. Part IV Future Steps: Algorithms That Can Improve Speech Intelligibility. Appendices. Index.