Theory and applications of digital speech processing
Responsibility Lawrence R. Rabiner, Ronald W. Schafer. Edition 1st ed. Imprint Upper Saddle River, NJ : Prentice Hall, c2011. Physical description xiv, 1042 p. : ill. (some col.) ; 25 cm.
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Items in Stacks | Call number | Note | Status |
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| TK7882 .S65 R32 2011 | Unknown |
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Description
Creators/Contributors
Author/Creator Rabiner, Lawrence R., 1943- Contributor Schafer, Ronald W., 1938-
Contents/Summary
- CHAPTER 1 Introduction to Digital Speech Processing 1 1.1 The Speech Signal 3 1.2 The Speech Stack 8 1.3 Applications of Digital Speech Processing 10 1.4 Comment on the References 15 1.5 Summary 17
- CHAPTER 2 Review of Fundamentals of Digital Signal Processing 18 2.1 Introduction 18 2.2 Discrete-Time Signals and Systems 18 2.3 Transform Representation of Signals and Systems 22 2.4 Fundamentals of Digital Filters 33 2.5 Sampling 44 2.6 Summary 56 Problems 56
- CHAPTER 3 Fundamentals of Human Speech Production 67 3.1 Introduction 67 3.2 The Process of Speech Production 68 3.3 Short-Time Fourier Representation of Speech 81 3.4 Acoustic Phonetics 86 3.5 Distinctive Features of the Phonemes of American English 108 3.6 Summary 110 Problems 110
- CHAPTER 4 Hearing, Auditory Models, and Speech Perception 124 4.1 Introduction 124 4.2 The Speech Chain 125 4.3 Anatomy and Function of the Ear 127 4.4 The Perception of Sound 133 4.5 Auditory Models 150 4.6 Human Speech Perception Experiments 158 4.7 Measurement of Speech Quality and Intelligibility 162 4.8 Summary 166 Problems 167
- CHAPTER 5 Sound Propagation in the Human Vocal Tract 170 5.1 The Acoustic Theory of Speech Production 170 5.2 Lossless Tube Models 200 5.3 Digital Models for Sampled Speech Signals 219 5.4 Summary 228 Problems 228
- CHAPTER 6 Time-Domain Methods for Speech Processing 239 6.1 Introduction 239 6.2 Short-Time Analysis of Speech 242 6.3 Short-Time Energy and Short-Time Magnitude 248 6.4 Short-Time Zero-Crossing Rate 257 6.5 The Short-Time Autocorrelation Function 265 6.6 The Modified Short-Time Autocorrelation Function 273 6.7 The Short-Time Average Magnitude Difference Function 275 6.8 Summary 277 Problems 278
- CHAPTER 7 Frequency-Domain Representations 287 7.1 Introduction 287 7.2 Discrete-Time Fourier Analysis 289 7.3 Short-Time Fourier Analysis 292 7.4 Spectrographic Displays 312 7.5 Overlap Addition Method of Synthesis 319 7.6 Filter Bank Summation Method of Synthesis 331 7.7 Time-Decimated Filter Banks 340 7.8 Two-Channel Filter Banks 348 7.9 Implementation of the FBS Method Using the FFT 358 7.10 OLA Revisited 365 7.11 Modifications of the STFT 367 7.12 Summary 379 Problems 380
- CHAPTER 8 The Cepstrum and Homomorphic Speech Processing 399 8.1 Introduction 399 8.2 Homomorphic Systems for Convolution 401 8.3 Homomorphic Analysis of the Speech Model 417 8.4 Computing the Short-Time Cepstrum and Complex Cepstrum of Speech 429 8.5 Homomorphic Filtering of Natural Speech 440 8.6 Cepstrum Analysis of All-Pole Models 456 8.7 Cepstrum Distance Measures 459 8.8 Summary 466 Problems 466
- CHAPTER 9 Linear Predictive Analysis of Speech Signals 473 9.1 Introduction 473 9.2 Basic Principles of Linear Predictive Analysis 474 9.3 Computation of the Gain for the Model 486 9.4 Frequency Domain Interpretations of Linear Predictive Analysis 490 9.5 Solution of the LPC Equations 505 9.6 The Prediction Error Signal 527 9.7 Some Properties of the LPC Polynomial A(z) 538 9.8 Relation of Linear Predictive Analysis to Lossless Tube Models 546 9.9 Alternative Representations of the LP Parameters 551 9.10 Summary 560 Problems 560
- CHAPTER 10 Algorithms for Estimating Speech Parameters 578 10.1 Introduction 578 10.2 Median Smoothing and Speech Processing 580 10.3 Speech-Background/Silence Discrimination 586 10.4 A Bayesian Approach to Voiced/Unvoiced/Silence Detection 595 10.5 Pitch Period Estimation (Pitch Detection) 603 10.6 Formant Estimation 635 10.7 Summary 645 Problems 645
- CHAPTER 11 Digital Coding of Speech Signals 663 11.1 Introduction 663 11.2 Sampling Speech Signals 667 11.3 A Statistical Model for Speech 669 11.4 Instantaneous Quantization 676 11.5 Adaptive Quantization 706 11.6 Quantizing of Speech Model Parameters 718 11.7 General Theory of Differential Quantization 732 11.8 Delta Modulation 743 11.9 Differential PCM (DPCM) 759 11.10 Enhancements for ADPCM Coders 768 11.11 Analysis-by-Synthesis Speech Coders 783 11.12 Open-Loop Speech Coders 806 11.13 Applications of Speech Coders 814 11.14 Summary 819 Problems 820
- CHAPTER 12 Frequency-Domain Coding of Speech and Audio 842 12.1 Introduction 842 12.2 Historical Perspective 844 12.3 Subband Coding 850 12.4 Adaptive Transform Coding 861 12.5 A Perception Model for Audio Coding 866 12.6 MPEG-1 Audio Coding Standard 881 12.7 Other Audio Coding Standards 894 12.8 Summary 894 Problems 895
- CHAPTER 13 Text-to-Speech Synthesis Methods 907 13.1 Introduction 907 13.2 Text Analysis 908 13.3 Evolution of Speech Synthesis Methods 914 13.4 Early Speech Synthesis Approaches 916 13.5 Unit Selection Methods 926 13.6 TTS Future Needs 942 13.7 Visual TTS 943 13.8 Summary 947 Problems 947
- CHAPTER 14 Automatic Speech Recognition and Natural Language Understanding 950 14.1 Introduction 950 14.2 Basic ASR Formulation 952 14.3 Overall Speech Recognition Process 953 14.4 Building a Speech Recognition System 954 14.5 The Decision Processes in ASR 957 14.6 Step 3: The Search Problem 971 14.7 Simple ASR System: Isolated Digit Recognition 972 14.8 Performance Evaluation of Speech Recognizers 974 14.9 Spoken Language Understanding 977 14.10 Dialog Management and Spoken Language Generation 980 14.11 User Interfaces 983 14.12 Multimodal User Interfaces 984 14.13 Summary 984 Problems 985 Appendices A Speech and Audio Processing Demonstrations 993 B Solution of Frequency-Domain Differential Equations 1005 Bibliography 1009 Index 1033.
- (source: Nielsen Book Data)
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