The late Ben Gold consulted at Massachusetts Institute of Technology and Lincoln Laboratory and taught at the University of California at Berkeley. He was the author of Digital Processing of Signals and the coauthor of Theory and Applications of Digital Signal Processing. Dr. Gold was an IEEE Fellow, member of the National Academy of Engineering, and recipient of several IEEE awards. Nelson Morgan is the Director of the International Computer Science Institute, an independent, not-for profit research laboratory affiliated with the University of California at Berkeley. Dr. Morgan is also Professor-in-Residence in the Electrical Engineering and Computer Sciences Department at UC Berkeley. Dr. Morgan is an IEEE Fellow.Dan Ellis is Associate Professor in the Electrical Engineering Department of Columbia University. Dr. Ellis's Laboratory for Recognition and Organization of Speech and Audio (LabROSA) investigates how to extract high-level information from audio, including speech recognition, music description, and environmental sound processing.

• PREFACE TO THE 2011 EDITION xxi CHAPTER 1 INTRODUCTION 1PART I HISTORICAL BACKGROUNDCHAPTER 2 SYNTHETIC A UDIO: A BRIEF HISTORY 9CHAPTER 3 SPEECH ANALYSIS AND SYNTHESIS OVERVIEW 21CHAPTER 4 BRIEF HISTORY OF AUTOMATIC SPEECH RECOGNITION 40CHAPTER 5 SPEECH-RECOGNITION OVERVIEW 59PART II MATHEMATICAL BACKGROUNDCHAPTER 6 DIGITAL SIGNAL PROCESSING 73CHAPTER 7 DIGITAL FILTERSAND DISCRETE FOURIER TRANSFORM 87CHAPTER 8 PATTERN CLASSIFICATION 105CHAPTER 9 STATISTICAL PATTERN CLASSIFICATION 124PART III ACOUSTICSCHAPTER 10 WAVE BASICS 141CHAPTER 11 ACOUSTIC TUBE MODELING OF SPEECH PRODUCTION 152CHAPTER 12 MUSICAL INSTRUMENT ACOUSTICS 158CHAPTER 13 ROOM ACOUSTICS 179PART IV AUDITORY PERCEPTIONCHAPTER 14  EAR PHYSIOLOGY 193CHAPTER 15 PSYCHOACOUSTICS 209CHAPTER 16 MODELS OF PITCH PERCEPTION 218CHAPTER 17 SPEECH PERCEPTION 232CHAPTER 18 HUMAN SPEECH RECOGNITION 250PART V SPEECH FEATURESCHAPTER 19 THE AUDITORY SYSTEM AS A FILTER BANK 263CHAPTER 20 THE CEPSTRUM AS A SPECTRAL ANALYZER 277CHAPTER 21 LINEAR PREDICTION 286PART VI A UTOMATIC SPEECH RECOGNITIONCHAPTER 22 FEATURE EXTRACTION FOR ASR 301CHAPTER 23 LINGUISTIC CATEGORIES FOR SPEECH RECOGNITION 319CHAPTER 24 DETERMINISTIC SEQUENCE RECOGNITION FOR ASR 337CHAPTER 25 STATISTICAL SEQUENCE RECOGNITION 350CHAPTER 26 STATISTICAL MODEL TRAINING 364CHAPTER 27 DISCRIMINANT ACOUSTIC PROBABILITY ESTIMATION 381CHAPTER 28 ACOUSTIC MODEL TRAINING: FURTHER TOPICS 394CHAPTER 29 SPEECH RECOGNITION AND UNDERSTANDING 416PART VII SYNTHESIS AND CODINGCHAPTER 30 SPEECH SYNTHESIS 431CHAPTER 31 PITCH DETECTION 455CHAPTER 32 VOCODERS 473CHAPTER 33 LOW-RATE VOCODERS 493CHAPTER 34 MEDIUM-RATE AND HIGH-RATE VOCODERS 505CHAPTER 35 PERCEPTUAL A UDIO CODING 531PART VIII OTHER APPLICATIONSCHAPTER 36 SOME ASPECTS OF COMPUTER MUSIC SYNTHESIS 553CHAPTER 37 MUSIC SIGNAL ANALYSIS 567CHAPTER 38 MUSIC RETRIEVAL 581CHAPTER 39 SOURCE SEPARATION 59CHAPTER 40 SPEECH TRANSFORMATIONS 617CHAPTER 41 SPEAKER VERIFICATION 633CHAPTER 42 SPEAKER DIARIZATION 644

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The late Ben Gold consulted at Massachusetts Institute of Technology and Lincoln Laboratory and taught at the University of California at Berkeley. He was the author of Digital Processing of Signals and the coauthor of Theory and Applications of Digital Signal Processing. Dr. Gold was an IEEE Fellow, member of the National Academy of Engineering, and recipient of several IEEE awards. Nelson Morgan is the Director of the International Computer Science Institute, an independent, not-for profit research laboratory affiliated with the University of California at Berkeley. Dr. Morgan is also Professor-in-Residence in the Electrical Engineering and Computer Sciences Department at UC Berkeley. Dr. Morgan is an IEEE Fellow.Dan Ellis is Associate Professor in the Electrical Engineering Department of Columbia University. Dr. Ellis's Laboratory for Recognition and Organization of Speech and Audio (LabROSA) investigates how to extract high-level information from audio, including speech recognition, music description, and environmental sound processing.

• PREFACE TO THE 2011 EDITION xxi CHAPTER 1 INTRODUCTION 1PART I HISTORICAL BACKGROUNDCHAPTER 2 SYNTHETIC A UDIO: A BRIEF HISTORY 9CHAPTER 3 SPEECH ANALYSIS AND SYNTHESIS OVERVIEW 21CHAPTER 4 BRIEF HISTORY OF AUTOMATIC SPEECH RECOGNITION 40CHAPTER 5 SPEECH-RECOGNITION OVERVIEW 59PART II MATHEMATICAL BACKGROUNDCHAPTER 6 DIGITAL SIGNAL PROCESSING 73CHAPTER 7 DIGITAL FILTERSAND DISCRETE FOURIER TRANSFORM 87CHAPTER 8 PATTERN CLASSIFICATION 105CHAPTER 9 STATISTICAL PATTERN CLASSIFICATION 124PART III ACOUSTICSCHAPTER 10 WAVE BASICS 141CHAPTER 11 ACOUSTIC TUBE MODELING OF SPEECH PRODUCTION 152CHAPTER 12 MUSICAL INSTRUMENT ACOUSTICS 158CHAPTER 13 ROOM ACOUSTICS 179PART IV AUDITORY PERCEPTIONCHAPTER 14  EAR PHYSIOLOGY 193CHAPTER 15 PSYCHOACOUSTICS 209CHAPTER 16 MODELS OF PITCH PERCEPTION 218CHAPTER 17 SPEECH PERCEPTION 232CHAPTER 18 HUMAN SPEECH RECOGNITION 250PART V SPEECH FEATURESCHAPTER 19 THE AUDITORY SYSTEM AS A FILTER BANK 263CHAPTER 20 THE CEPSTRUM AS A SPECTRAL ANALYZER 277CHAPTER 21 LINEAR PREDICTION 286PART VI A UTOMATIC SPEECH RECOGNITIONCHAPTER 22 FEATURE EXTRACTION FOR ASR 301CHAPTER 23 LINGUISTIC CATEGORIES FOR SPEECH RECOGNITION 319CHAPTER 24 DETERMINISTIC SEQUENCE RECOGNITION FOR ASR 337CHAPTER 25 STATISTICAL SEQUENCE RECOGNITION 350CHAPTER 26 STATISTICAL MODEL TRAINING 364CHAPTER 27 DISCRIMINANT ACOUSTIC PROBABILITY ESTIMATION 381CHAPTER 28 ACOUSTIC MODEL TRAINING: FURTHER TOPICS 394CHAPTER 29 SPEECH RECOGNITION AND UNDERSTANDING 416PART VII SYNTHESIS AND CODINGCHAPTER 30 SPEECH SYNTHESIS 431CHAPTER 31 PITCH DETECTION 455CHAPTER 32 VOCODERS 473CHAPTER 33 LOW-RATE VOCODERS 493CHAPTER 34 MEDIUM-RATE AND HIGH-RATE VOCODERS 505CHAPTER 35 PERCEPTUAL A UDIO CODING 531PART VIII OTHER APPLICATIONSCHAPTER 36 SOME ASPECTS OF COMPUTER MUSIC SYNTHESIS 553CHAPTER 37 MUSIC SIGNAL ANALYSIS 567CHAPTER 38 MUSIC RETRIEVAL 581CHAPTER 39 SOURCE SEPARATION 59CHAPTER 40 SPEECH TRANSFORMATIONS 617CHAPTER 41 SPEAKER VERIFICATION 633CHAPTER 42 SPEAKER DIARIZATION 644

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The late Ben Gold consulted at Massachusetts Institute of Technology and Lincoln Laboratory and taught at the University of California at Berkeley. He was the author of Digital Processing of Signals and the coauthor of Theory and Applications of Digital Signal Processing. Dr. Gold was an IEEE Fellow, member of the National Academy of Engineering, and recipient of several IEEE awards. Nelson Morgan is the Director of the International Computer Science Institute, an independent, not-for profit research laboratory affiliated with the University of California at Berkeley. Dr. Morgan is also Professor-in-Residence in the Electrical Engineering and Computer Sciences Department at UC Berkeley. Dr. Morgan is an IEEE Fellow.Dan Ellis is Associate Professor in the Electrical Engineering Department of Columbia University. Dr. Ellis's Laboratory for Recognition and Organization of Speech and Audio (LabROSA) investigates how to extract high-level information from audio, including speech recognition, music description, and environmental sound processing.

• PREFACE TO THE 2011 EDITION xxi CHAPTER 1 INTRODUCTION 1PART I HISTORICAL BACKGROUNDCHAPTER 2 SYNTHETIC A UDIO: A BRIEF HISTORY 9CHAPTER 3 SPEECH ANALYSIS AND SYNTHESIS OVERVIEW 21CHAPTER 4 BRIEF HISTORY OF AUTOMATIC SPEECH RECOGNITION 40CHAPTER 5 SPEECH-RECOGNITION OVERVIEW 59PART II MATHEMATICAL BACKGROUNDCHAPTER 6 DIGITAL SIGNAL PROCESSING 73CHAPTER 7 DIGITAL FILTERSAND DISCRETE FOURIER TRANSFORM 87CHAPTER 8 PATTERN CLASSIFICATION 105CHAPTER 9 STATISTICAL PATTERN CLASSIFICATION 124PART III ACOUSTICSCHAPTER 10 WAVE BASICS 141CHAPTER 11 ACOUSTIC TUBE MODELING OF SPEECH PRODUCTION 152CHAPTER 12 MUSICAL INSTRUMENT ACOUSTICS 158CHAPTER 13 ROOM ACOUSTICS 179PART IV AUDITORY PERCEPTIONCHAPTER 14  EAR PHYSIOLOGY 193CHAPTER 15 PSYCHOACOUSTICS 209CHAPTER 16 MODELS OF PITCH PERCEPTION 218CHAPTER 17 SPEECH PERCEPTION 232CHAPTER 18 HUMAN SPEECH RECOGNITION 250PART V SPEECH FEATURESCHAPTER 19 THE AUDITORY SYSTEM AS A FILTER BANK 263CHAPTER 20 THE CEPSTRUM AS A SPECTRAL ANALYZER 277CHAPTER 21 LINEAR PREDICTION 286PART VI A UTOMATIC SPEECH RECOGNITIONCHAPTER 22 FEATURE EXTRACTION FOR ASR 301CHAPTER 23 LINGUISTIC CATEGORIES FOR SPEECH RECOGNITION 319CHAPTER 24 DETERMINISTIC SEQUENCE RECOGNITION FOR ASR 337CHAPTER 25 STATISTICAL SEQUENCE RECOGNITION 350CHAPTER 26 STATISTICAL MODEL TRAINING 364CHAPTER 27 DISCRIMINANT ACOUSTIC PROBABILITY ESTIMATION 381CHAPTER 28 ACOUSTIC MODEL TRAINING: FURTHER TOPICS 394CHAPTER 29 SPEECH RECOGNITION AND UNDERSTANDING 416PART VII SYNTHESIS AND CODINGCHAPTER 30 SPEECH SYNTHESIS 431CHAPTER 31 PITCH DETECTION 455CHAPTER 32 VOCODERS 473CHAPTER 33 LOW-RATE VOCODERS 493CHAPTER 34 MEDIUM-RATE AND HIGH-RATE VOCODERS 505CHAPTER 35 PERCEPTUAL A UDIO CODING 531PART VIII OTHER APPLICATIONSCHAPTER 36 SOME ASPECTS OF COMPUTER MUSIC SYNTHESIS 553CHAPTER 37 MUSIC SIGNAL ANALYSIS 567CHAPTER 38 MUSIC RETRIEVAL 581CHAPTER 39 SOURCE SEPARATION 59CHAPTER 40 SPEECH TRANSFORMATIONS 617CHAPTER 41 SPEAKER VERIFICATION 633CHAPTER 42 SPEAKER DIARIZATION 644

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