Discrete–Time Processing of Speech Signals

Electrical Engineering Discrete–Time Processing of Speech Signals Commercial applications of speech processing and recognition are fast becoming a growth industry that will shape the next decade. Now students and practicing engineers of signal processing can find in a single volume the fundamentals essential to understanding this rapidly developing field. IEEE Press is pleased to publish a classic reissue of Discrete–Time Processing of Speech Signals. Specially featured in this reissue is the addition of valuable World Wide Web links to the latest speech data references. This landmark book offers a balanced discussion of both the mathematical theory of digital speech signal processing and critical contemporary applications. The authors provide a comprehensive view of all major modern speech processing areas: speech production physiology and modeling, signal analysis techniques, coding, enhancement, quality assessment, and recognition. You will learn the principles needed to understand advanced technologies in speech processing—from speech coding for communications systems to biomedical applications of speech analysis and recognition. Ideal for self–study or as a course text, this far–reaching reference book offers an extensive historical context for concepts under discussion, end–of–chapter problems, and practical algorithms. Discrete–Time Processing of Speech Signals is the definitive resource for students, engineers, and scientists in the speech processing field.

Spis treści:
Preface to the IEEE Edition.
Preface.
Acronyms and Abbreviations.
SIGNAL PROCESSING BACKGROUND.
Propaedeutic.
SPEECH PRODUCTION AND MODELLING.
Fundamentals of Speech Science.
Modeling Speech Production.
ANALYSIS TECHNIQUES.
Short–Term Processing of Speech.
Linear Prediction Analysis.
Cepstral Analysis.
CODING, ENHANCEMENT AND QUALITY ASSESSMENT.
Speech Coding and Synthesis.
Sp eech Enhancement.
Speech Quality Assessment.
RECOGNITION.
The Speech Recognition Problem.
Dynamic Time Warping.
The Hidden Markov Model.
Language Modeling.
The Artificial Neural Network.
Index.

Nota biograficzna:
John R. (Jack) Deller, Jr. is professor of electrical and computer engineering at Michigan State University where he directs the Speech Processing Laboratory. He received the 1998 IEEE Signal Processing Magazine Best Paper Award and the 1997 IEEE Signal Processing Society Meritorious Service Award for his six–year service as editor in chief of the IEEE Signal Processing Magazine. Dr. Deller is the coauthor of Digital Signal Processing and the Microcontroller (Prentice Hall, 1999) and currently serves as associate editor of the IEEE Transactions on Speech and Audio Processing. He is a Fellow of the IEEE.
John H. L. Hansen is an associate professor at the University of Colorado at Boulder; he holds appointments in the Department of Speech, Language, and Hearing Sciences and in the Department of Electrical and Computer Engineering. Dr. Hansen serves as associate director for the Center for Spoken Language Understanding (CSLU) and director of research activities of the Robust Speech Processing Laboratory at CSLU. He has served as technical advisor to the U.S. delegate for NATO, and he is associate editor of the IEEE Transactions on Speech and Audio Processing and of the IEEE Signal Processing Letters. Dr. Hansen received the 1990 National Science Foundation Research Initiation Award and has been named a Lilly Foundation Teaching Fellow for contributions to the advancement of engineering education.
John G. Proakis is a faculty member of the Electrical and Computer Engineering Department at Northeastern University. His professional experience is in the general area of digital communications and digital signal processing. Dr. Proakis is the author of Digital C ommunications (McGraw–Hill, 3rd ed., 1995) and the coauthor of Introduction to Digital Signal Processing (Prentice Hall, 3rd ed., 1996); Advanced Digital Signal Processing (Macmillan, 1992); Communication Systems Engineering (Prentice Hall, 1994); Digital Signal Processing Using MATLAB (PWS, 1997); and Contemporary Communication Systems Using MATLAB (PWS, 1998). He is a Life Fellow of the IEEE.

Okładka tylna:
Electrical Engineering Discrete–Time Processing of Speech Signals Commercial applications of speech processing and recognition are fast becoming a growth industry that will shape the next decade. Now students and practicing engineers of signal processing can find in a single volume the fundamentals essential to understanding this rapidly developing field. IEEE Press is pleased to publish a classic reissue of Discrete–Time Processing of Speech Signals. Specially featured in this reissue is the addition of valuable World Wide Web links to the latest speech data references. This landmark book offers a balanced discussion of both the mathematical theory of digital speech signal processing and critical contemporary applications. The authors provide a comprehensive view of all major modern speech processing areas: speech production physiology and modeling, signal analysis techniques, coding, enhancement, quality assessment, and recognition. You will learn the principles needed to understand advanced technologies in speech processing—from speech coding for communications systems to biomedical applications of speech analysis and recognition. Ideal for self–study or as a course text, this far–reaching reference book offers an extensive historical context for concepts under discussion, end–of–chapter problems, and practical algorithms. Discrete–Time Processing of Speech Signals is the definitive resource for students, engineers, and scientists in the speech processing field.