Spoken Language Processing_ A Guide to Theory, Algorithm, and System Development [Huang, Acero & Hon 2001-05-05].pdf

TABLE OF CONTENTS

1. INTRODUCTION ................................................................................................... 1

1.1.

M OTIVATIONS ....................................................................................................... 2

1.1.1.

Spoken Language Interface ................................................................... 2

1.1.2.

Speech-to-speech Translation ................................................................ 3

1.1.3.

Knowledge Partners ............................................................................... 3

1.2.

S POKEN L ANGUAGE S YSTEM A RCHITECTURE ........................................................ 4

1.2.1.

Automatic Speech Recognition .............................................................. 4

1.2.2.

Text-to-Speech Conversion .................................................................... 6

1.2.3.

Spoken Language Understanding .......................................................... 7

1.3.

B OOK O RGANIZATION ............................................................................................ 9

1.3.1.

Part I: Fundamental Theory .................................................................. 9

1.3.2.

Part II: Speech Processing .................................................................... 9

1.3.3.

Part III: Speech Recognition ............................................................... 10

1.3.4.

Part IV: Text-to-Speech Systems .......................................................... 10

1.3.5.

Part V: Spoken Language Systems ...................................................... 10

1.4.

T ARGET A UDIENCES ............................................................................................. 11

1.5.

H ISTORICAL P ERSPECTIVE AND F URTHER R EADING ............................................. 11

PART I: FUNDAMENTAL THEORY

2. SPOKEN LANGUAGE STRUCTURE ......................................................... 19

2.1.

S OUND AND H UMAN S PEECH S YSTEMS ................................................................ 21

2.1.1.

Sound ................................................................................................... 21

2.1.2.

Speech Production ............................................................................... 24

2.1.3.

Speech Perception ................................................................................ 28

2.2.

P HONETICS AND P HONOLOGY ............................................................................... 36

2.2.1.

Phonemes ............................................................................................. 36

2.2.2.

The Allophone: Sound and Context ..................................................... 47

2.2.3.

Speech Rate and Coarticulation .......................................................... 49

2.3.

S YLLABLES AND W ORDS ...................................................................................... 50

2.3.1.

Syllables ............................................................................................... 51

2.3.2.

Words ................................................................................................... 52

2.4.

S YNTAX AND S EMANTICS ..................................................................................... 57

2.4.1.

Syntactic Constituents .......................................................................... 58

2.4.2.

Semantic Roles ..................................................................................... 63

2.4.3.

Lexical Semantics ................................................................................ 64

2.4.4.

Logical Form ....................................................................................... 66

2.5.

H ISTORICAL P ERSPECTIVE AND F URTHER R EADING ............................................. 68

TABLE OF CONTENTS

3. PROBABILITY, STATISTICS AND INFORMATION THEORY ..73

3.1.

P ROBABILITY T HEORY ......................................................................................... 74

3.1.1.

Conditional Probability And Bayes' Rule ............................................ 75

3.1.2.

Random Variables ................................................................................ 77

3.1.3.

Mean and Variance .............................................................................. 79

3.1.4.

Covariance and Correlation ................................................................ 83

3.1.5.

Random Vectors and Multivariate Distributions ................................. 84

3.1.6.

Some Useful Distributions ................................................................... 85

3.1.7.

Gaussian Distributions ........................................................................ 92

3.2.

E STIMATION T HEORY ........................................................................................... 98

3.2.1.

Minimum/Least Mean Squared Error Estimation ................................ 99

3.2.2.

Maximum Likelihood Estimation ....................................................... 104

3.2.3.

Bayesian Estimation and MAP Estimation ........................................ 108

3.3.

S IGNIFICANCE TESTING ....................................................................................... 114

3.3.1.

Level of Significance .......................................................................... 114

3.3.2.

Normal Test (Z-Test) .......................................................................... 116

Goodness-of-Fit Test ................................................................... 117

3.3.3.

3.3.4.

Matched-Pairs Test ............................................................................ 119

3.4.

I NFORMATION T HEORY ...................................................................................... 121

3.4.1.

Entropy .............................................................................................. 121

3.4.2.

Conditional Entropy .......................................................................... 124

3.4.3.

The Source Coding Theorem ............................................................. 125

3.4.4.

Mutual Information and Channel Coding .......................................... 127

3.5.

H ISTORICAL P ERSPECTIVE AND F URTHER R EADING ........................................... 129

4. PATTERN RECOGNITION ........................................................................... 133

4.1.

B AYES D ECISION T HEORY .................................................................................. 134

4.1.1.

Minimum-Error-Rate Decision Rules ................................................ 135

4.1.2.

Discriminant Functions ..................................................................... 138

4.2.

H OW TO C ONSTRUCT C LASSIFIERS ..................................................................... 140

4.2.1.

Gaussian Classifiers .......................................................................... 142

4.2.2.

The Curse of Dimensionality .............................................................. 144

4.2.3.

Estimating the Error Rate .................................................................. 146

4.2.4.

Comparing Classifiers ....................................................................... 148

4.3.

D ISCRIMINATIVE T RAINING ................................................................................ 150

4.3.1.

Maximum Mutual Information Estimation ......................................... 150

4.3.2.

Minimum-Error-Rate Estimation ....................................................... 156

4.3.3.

Neural Networks ................................................................................ 158

4.4.

U NSUPERVISED E STIMATION M ETHODS ............................................................. 163

4.4.1.

Vector Quantization ........................................................................... 164

4.4.2.

The EM Algorithm ............................................................................. 170

4.4.3.

Multivariate Gaussian Mixture Density Estimation ........................... 172

TABLE OF CONTENTS

iii

4.5.

C LASSIFICATION AND R EGRESSION T REES .......................................................... 176

4.5.1.

Choice of Question Set ....................................................................... 177

4.5.2.

Splitting Criteria ................................................................................ 179

4.5.3.

Growing the Tree ............................................................................... 181

4.5.4.

Missing Values and Conflict Resolution ............................................ 182

4.5.5.

Complex Questions ............................................................................ 183

4.5.6.

The Right-Sized Tree .......................................................................... 185

4.6.

H ISTORICAL P ERSPECTIVE AND F URTHER R EADING ........................................... 190

PART II SPEECH PROCESSING

5. DIGITAL SIGNAL PROCESSING .............................................................. 201

5.1.

D IGITAL S IGNALS AND S YSTEMS ........................................................................ 202

5.1.1.

Sinusoidal Signals .............................................................................. 203

5.1.2.

Other Digital Signals ......................................................................... 206

5.1.3.

Digital Systems .................................................................................. 206

5.2.

C ONTINUOUS -F REQUENCY T RANSFORMS ........................................................... 209

5.2.1.

The Fourier Transform ...................................................................... 209

5.2.2.

Z-Transform ....................................................................................... 211

5.2.3.

Z-Transforms of Elementary Functions ............................................. 212

5.2.4.

Properties of the Z and Fourier Transform ....................................... 215

5.3.

D ISCRETE -F REQUENCY T RANSFORMS ................................................................ 216

5.3.1.

The Discrete Fourier Transform (DFT) ............................................. 218

5.3.2.

Fourier Transforms of Periodic Signals ............................................ 219

5.3.3.

The Fast Fourier Transform (FFT) .................................................... 222

5.3.4.

Circular Convolution ......................................................................... 227

5.3.5.

The Discrete Cosine Transform (DCT) .............................................. 228

5.4.

D IGITAL F ILTERS AND W INDOWS ........................................................................ 229

5.4.1.

The Ideal Low-Pass Filter ................................................................. 229

5.4.2.

Window Functions ............................................................................. 230

5.4.3.

FIR Filters .......................................................................................... 232

5.4.4.

IIR Filters ........................................................................................... 238

5.5.

D IGITAL P ROCESSING OF A NALOG S IGNALS ........................................................ 242

5.5.1.

Fourier Transform of Analog Signals ................................................ 242

5.5.2.

The Sampling Theorem ...................................................................... 243

5.5.3.

Analog-to-Digital Conversion ........................................................... 245

5.5.4.

Digital-to-Analog Conversion ........................................................... 246

5.6.

M ULTIRATE S IGNAL P ROCESSING ....................................................................... 247

5.6.1.

Decimation ......................................................................................... 248

5.6.2.

Interpolation ...................................................................................... 249

5.6.3.

Resampling ........................................................................................ 250

5.7.

F ILTERBANKS ..................................................................................................... 250

5.7.1.

Two-Band Conjugate Quadrature Filters .......................................... 250

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