Discrete-Time Speech Signal Processing: Principles and Practice

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9780132429429: Discrete-Time Speech Signal Processing: Principles and Practice
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Essential principles, practical examples, current applications, and leading-edge research.

In this book, Thomas F. Quatieri presents the field's most intensive, up-to-date tutorial and reference on discrete-time speech signal processing. Building on his MIT graduate course, he introduces key principles, essential applications, and state-of-the-art research, and he identifies limitations that point the way to new research opportunities.

Quatieri provides an excellent balance of theory and application, beginning with a complete framework for understanding discrete-time speech signal processing. Along the way, he presents important advances never before covered in a speech signal processing text book, including sinusoidal speech processing, advanced time-frequency analysis, and nonlinear aeroacoustic speech production modeling. Coverage includes:

  • Speech production and speech perception: a dual view
  • Crucial distinctions between stochastic and deterministic problems
  • Pole-zero speech models
  • Homomorphic signal processing
  • Short-time Fourier transform analysis/synthesis
  • Filter-bank and wavelet analysis/synthesis
  • Nonlinear measurement and modeling techniques

The book's in-depth applications coverage includes speech coding, enhancement, and modification; speaker recognition; noise reduction; signal restoration; dynamic range compression, and more. Principles of Discrete-Time Speech Processing also contains an exceptionally complete series of examples and Matlab exercises, all carefully integrated into the book's coverage of theory and applications.

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About the Author:

THOMAS F. QUATIERI is a Senior Member of the Technical Staff at MIT's Lincoln Laboratory in Lexington, MA. He is involved in digital signal processing for speech and audio modification, coding, enhancement, and speaker recognition, and he developed MIT's graduate course in Digital Speech Processing. Quatieri's publications and papers include Speech Analysis/Synthesis Based on a Sinusoidal Representation, winner of the 1990 IEEE Signal Processing Society's Senior Award, and Energy Separation in Signal Modulations with Application to Speech Analysis, winner of the 1994 IEEE Signal Processing Society's Senior Award and the 1995 IEEE W.R.G. Baker Prize Award. A Fellow of the IEEE and a member of Sigma Xi, Tau Beta Pi, Eta Kappa Nu, and the Acoustical Society of America, he holds S.M., E.E., and Sc.D. degrees from MIT.

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Preface

This text is in part an outgrowth of my MIT graduate course Digital Speech Signal Processing, which I have taught since the Fall of 1990, and in part a result of my research at MIT Lincoln Laboratory. As such, principles are never too distant from practice; theory is often followed by applications, both past and present. This text is also an outgrowth of my childhood wonder in the blending of signal and symbol processing, sound, and technology. I first felt this fascination in communicating with two cans coupled by twine, in playing with a toy Morse code, and in adventuring through old ham radio equipment in my family's basement. My goals in this book are to provide an intensive tutorial on the principles of discrete-time speech signal processing, to describe the state-of-the-art in speech signal processing research and its applications, and to pass on to the reader my continued wonder for this rapidly evolving field.

The text consists of fourteen chapters that are outlined in detail in Chapter 1. The "theory" component of the book falls within Chapters 2-11, while Chapters 12-14 consist primarily of the application areas of speech coding and enhancement, and speaker recognition. Other applications are introduced throughout Chapters 2-11, such as speech modification, noise reduction, signal restoration, and dynamic range compression. A broader range of topics that include speech and language recognition is not covered; to do so would result in a survey book that does not fill the current need in this field. The style of the text is to show not only when speech modeling and processing methods succeed, but also to describe limitations of the methods. This style makes the reader question established ideas and reveals where advancement is needed. An important tenet in this book is that anomaly in observation is crucial for advancement; as reflected by the late philosopher Thomas Kuhn: "Discovery commences with the awareness of anomaly, i.e., with the recognition that nature has somehow violated the paradigm-induced expectations that govern normal science."1

The text body is strongly supplemented with examples and exercises. Each exercise set contains a number of MATLAB problems that provide hands-on experience with speech signals and processing methods. Scripts, workspaces, and signals, required for the MATLAB exercises, are located on the Prentice Hall companion website (http://www.phptr.com/quatieri/). Also on this website are audio demonstrations that illustrate a variety of principles and applications from each chapter, including time-scale modification of the phrase "as time goes by" shown on the front cover of this book. The book is structured so that application areas that are not covered as separate topics are either presented as examples or exercises, e.g., speaker separation by sinusoidal modeling and restoration of old acoustic recordings by homomorphic processing. In my MIT speech processing course, I found this approach to be very effective, especially since such examples and exercises are fascinating demonstrations of the theory and can provide a glimpse of state-of-the-art applications.

The book is also structured so that topics can be covered on different levels of depth and breadth. For example, a one-semester course on discrete-time speech signal processing could be taught with an emphasis on fundamentals using Chapters 2-9. To focus on the speech coding application, one can include Chapter 12, but also other applications as examples and exercises. In a two-semester course, greater depth could be given to fundamentals in the first semester, using Chapters 2-9. In the second semester, a focus could then be given to advanced theories and applications of Chapters 10-14, with supplementary material on speech recognition.

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