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This handbook is designed to play a fundamental role in sustainable progress in speech research and development. It is the authoritative desk reference of one of tomorrow's breakthrough technologies.

From common consumer products such as cell phones and MP3 players to more sophisticated projects such as human-machine interfaces and responsive robots, speech technologies are now everywhere. Many think that it is just a matter of time before more applications of the science of speech become inescapable in our daily life. This handbook is meant to play a fundamental role for sustainable progress in speech research and development. Springer Handbook of Speech Processing targets three categories of readers: graduate students, professors and active researchers in academia and research labs, and engineers in industry who need to understand or implement some specific algorithms for their speech-related products. The handbook could also be used as a sourcebook for one or more graduate courses on signal processing for speech and different aspects of speech processing and applications. A quickly accessible source of application-oriented, authoritative and comprehensive information about these technologies, it combines the established knowledge derived from research in such fast evolving disciplines as Signal Processing and Communications, Acoustics, Computer Science and Linguistics.

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'Foreword by J. L. Flanagan
Chap. 1 Introduction to Speech Processing

Part A: Production, Perception, and Modeling of Speech (M. M. Sondhi)
Part A describes the contemporary views on phonatory and articulatory mechanisms of humans to illustrate the physiological processes of speech production. It also describes the nonlinear cochlear speech processing in auditory masking, the perception of speech and sound by humans, and various methods for speech quality assessment with a focus on standardized methods.
Chap. 2 Physiological Processes of Speech Production
Chap. 3 Nonlinear Cochlear Signal Processing and Masking in Speech Perception
Chap. 4 Perception of Speech and Sound
Chap. 5 Speech Quality Estimation
Part B: Signal Processing for Speech (Y. Huang, J. Benesty)
Part B gives a large number of signal processing concepts and algorithms that are widely used in speech processing and in the applications of speech.
Chap. 6 Wiener and Adaptive Filters
Chap. 7 Linear Prediction
Chap. 8 Kalman Filter
Chap. 9 Homomorphic Systems and Cepstrum Analysis of Speech
Chap. 10 Pitch and Voicing Determination of Speech with an Extension Toward Music Signals
Chap. 11 Formant Estimation and Tracking
Chap. 12 The STFT, Sinusoidal Models, and Speech Modification
Chap. 13 Adaptive Blind Multichannel Identification
Part C: Speech Coding (W. B. Kleijn)
Part C discusses the attributes of speech coders as well as the underlying principles that determine their behavior and architecture. Coders for both traditional and packet networks are discussed, as well as low-bit-rate speech coding, various speech coding standards, and perceptual audio coders.
Chap. 14 Principles of Speech Coding
Chap. 15 Voice over IP: Speech Transmission over Packet Networks
Chap. 16 Low-Bit-Rate Speech Coding
Chap. 17 Analysis-by-Synthesis Speech Coding
Chap. 18 Perceptual Audio Coding of Speech Signals

Part D: Text-to-Speech Synthesis (S. Narayanan)
Part D presents different techniques for speech synthesis, including rule-based, corpus-based, and a combination of both. Linguistic analysis and prosodic processing, which are important parts of a text-to-speech (TTS) system, are reviewed. Other aspects of interest for TTS such as voice transformation and synthesis of expressive speech are also discussed.
Chap. 19 Basic Principles of Speech Synthesis
Chap. 20 Rule-Based Speech Synthesis
Chap. 21 Corpus-Based Speech Synthesis
Chap. 22 Linguistic Processing for Speech Synthesis
Chap. 23 Prosodic Processing
Chap. 24 Voice Transformation
Chap. 25 Expressive/Affective Speech Synthesis
Part E: Speech Recognition (L. Rabiner, B.-H. Juang)
Part E describes the most important speech recognition technologies. The approach based on the powerful hidden Markov models is generously presented and some other promising approaches are outlined. The robustness issues concerning the acoustical environment are studied. Finally, several fundamental applications are also discussed.
Chap. 26 Historical Perspective of the Field of ASR/NLU
Chap. 27 HMMs and Related Speech Technologies
Chap. 28 Speech Recognition with Weighted Finite-State Transducers
Chap. 29 A Machine Learning Framework for Spoken-Dialog Classification
Chap. 30 Towards Superhuman Speech Recognition
Chap. 31 Natural Language Understanding
Chap. 32 Transcription and Distillation of Spontaneous Speech
Chap. 33 Environmental Robustness
Chap. 34 The Business of Speech Technologies
Chap. 35 Spoken Dialog Systems
Part F: Speaker Recognition (S. Parthasarathy)
Part F develops the field of speaker recognition. It covers text-dependent and text-independent speaker recognition and their applications.
Chap. 36 Overview of Speaker Recognition
Chap. 37 Text-Dependent Speaker Recognition
Chap. 38 Text-Independent Speaker Recognition
Part G: Language Recognition (C.-H. Lee)
Part G provides an overview on principles of state-of-the-art language recognition a

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