When Speech and Audio Signal Processing published in 1999,
it stood out from its competition in its breadth of coverage and
its accessible, intutiont-based style. This book was aimed at
individual students and engineers excited about the broad span of
audio processing and curious to understand the available
techniques. Since then, with the advent of the i Pod in 2001,
the field of digital audio and music has exploded, leading to a
much greater interest in the technical aspects of audio
processing.
This Second Edition will update and revise the original
book to augment it with new material describing both the enabling
technologies of digital music distribution (most significantly the
MP3) and a range of exciting new research areas in automatic music
content processing (such as automatic transcription, music
similarity, etc.) that have emerged in the past five years, driven
by the digital music revolution.
New chapter topics include:
* Psychoacoustic Audio Coding, describing MP3 and related
audio coding schemes based on psychoacoustic masking of
quantization noise
* Music Transcription, including automatically deriving
notes, beats, and chords from music signals.
* Music Information Retrieval, primarily focusing on
audio-based genre classification, artist/style identification, and
similarity estimation.
* Audio Source Separation, including multi-microphone
beamforming, blind source separation, and the perception-inspired
techniques usually referred to as Computational Auditory Scene
Analysis (CASA).
Inhaltsverzeichnis
PREFACE TO THE 2011 EDITION xxi
CHAPTER 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
Über den Autor
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
(Lab ROSA) investigates how to extract high-level information from
audio, including speech recognition, music description, and
environmental sound processing.
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