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 approaches. Language characterization, identification, and modeling are addressed. Vector space characterization approaches to converting speech utterances into spoken document vectors for modeling and classification are also presented.
Chap. 39 Principle of Spoken Language Recognition
Chap. 40 Spoken Language Characterization
Chap. 41 Automatic Language Recognition via Spectral and Token Based Approaches
Chap. 42 Vector Based Spoken Language Classification
Part H: Speech Enhancement (J. Chen, S. Gannot, J. Benesty)
Part H develops all classical aspects of speech enhancement: noise reduction, dereverberation, echo cancellation, feedback control, and active noise control.
Chap. 43 Fundamentals of Noise Reduction
Chap. 44 Spectral Enhancement methods
Chap. 45 Echo Cancellation
Chap. 46 Dereverberation
Chap. 47 Adaptive Beamforming and Postfiltering
Chap. 48 Feedback Control in Hearing Aids
Chap. 49 Active Noise Control
Part I: Multichannel Speech Processing (J. Benesty, I. Cohen, Y. Huang)
Part I presents modern aspects of multichannel processing, for acoustic scene analysis, speech acquisition and presentation, when a large number of microphones and loudspeakers are available.
Chap. 50 Microphone Arrays
Chap. 51 Time Delay Estimation and Source Localization
Chap. 52 Convolutive Blind Source Separation Methods
Chap. 53 Sound Field Reproduction
About the Authors