Speech and Audio Signal Processing: Processing and Perception of Speech and Music

Helps readers develop an intuitive understanding of audio signal processing
Acclaimed for its breadth of coverage as well as its clear, accessible presentation, Speech and Audio Signal Processing examines how machines and humans process audio signals, with an emphasis on speech and music. It begins with basic principles and then explains how these principles set the foundation for a wide range of applications. Moreover, the book is organized into a series of short chapters, offering readers a succinct overview of the range of topics that together represent the current state of knowledge in the field.
This Second Edition brings the book fully up to date with the explosive growth in audio processing technology, including the latest advances in digital music processing and distribution. New topics include:
Psychoacoustic audio coding, examining MP3 and related audio coding schemes that are based on the psychoacoustic masking of quantization noise
Music transcription, explaining how notes, beats, and chords can be automatically derived from music signals
Music information retrieval, exploring audio–based genre classification, artist and style identification, and similarity estimation
Audio source separation, describing multi–microphone beamforming, blind source separation, and perception–inspired techniques
Throughout the book, the authors present both human and machine strategies for accomplishing audio processing tasks. Readers will discover that, in many cases, human strategies can provide the inspiration for the development of machine strategies.
Speech and Audio Signal Processing is recommended for anyone who needs to understand the technologies underlying some of today′s most cutting–edge applications, including speech recognition, audio compression, music synthesis, and diarization.

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

Nota biograficzna:
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.

Okładka tylna:
Helps readers develop an intuitive understanding of audio signal processing
Acclaimed for its breadth of coverage as well as its clear, accessible presentation, Speech and Audio Signal Processing examines how machines and humans process audio signals, with an emphasis on speech and music. It begins with basic principles and then explains how these principles set the foundation for a wide range of applications. Moreover, the book is organized into a series of short chapters, offering readers a succinct overview of the range of topics that together represent the current state of knowledge in the field.
This Second Edition brings the book fully up to date with the explosive growth in audio processing technology, including the latest advances in digital music processing and distribution. New topics include:
Psychoacoustic audio coding, examining MP3 and related audio coding schemes that are based on the psychoacoustic masking of quantization noise
Music transcription, explaining how notes, beats, and chords can be automatically derived from music signals
Music information retrieval, exploring audio–based genre classification, artist and style identification, and similarity estimation
Audio source separation, describing multi–microphone beamforming, blind source separation, and perception–inspired techniques
Throughout the book, the authors present both human and machine strategies for accomplishing audio processing tasks. Readers will discover that, in many cases, human strategies can provide the inspiration for the development of machine strategies.
Speech and Audio Signal Processing is recommended for anyone who needs to understand the technologies underlying some of today′s most cutting–edge applications, including speech recognition, audio compression, music synthesis, and diarization.