Springer handbook of speech processing with 113 tables
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| 245 | 1 | 0 | |a Springer handbook of speech processing |b with 113 tables |c Jacob Benesty ... (eds.) |
| 246 | 1 | 3 | |a Handbook of speech processing |
| 264 | 1 | |a Berlin [u.a.] |b Springer |c 2008 | |
| 300 | |a XXXVI, 1176 S. |b Ill., graph. Darst. |e 1 DVD-ROM (12 cm) | ||
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| adam_text | Contents
List of Abbreviations xxxi
1 Introduction to Speech Processing
J. Benesty, M.M. Sondhi, Y. Huang 1
1.1 A Brief History of Speech Processing 1
1.2 Applications of Speech Processing 2
1.3 Organization of the Handbook 4
References 4
Part A Production, Perception, and Modeling of Speech
2 Physiological Processes of Speech Production
K. Honda 7
2.1 Overview of Speech Apparatus 7
2.2 Voice Production Mechanisms 8
2.3 Articulatory Mechanisms 14
2.4 Summary 24
References 25
3 Nonlinear Cochlear Signal Processing and Masking
in Speech Perception
J. B. Allen 27
3.1 Basics 27
3.2 The Nonlinear Cochlea 35
3.3 Neural Masking 45
3.4 Discussion and Summary 55
References 56
4 Perception of Speech and Sound
B. Kollmeier, T. Brand, B. Meyer 61
4.1 Basic Psychoacoustic Quantities 62
4.2 Acoustical Information Required for Speech Perception 70
4.3 Speech Feature Perception 74
References 81
5 Speech Quality Assessment
V. Grancharov, W. B. Kleijn 83
5.1 Degradation Factors Affecting Speech Quality 84
5.2 Subjective Tests 85
5.3 Objective Measures 90
5.4 Conclusions 95
References 96
Part B Signal Processing for Speech
6 Wiener and Adaptive Filters
J. Benesty, Y. Huang,J. Chen 103
6.1 Overview 103
6.2 Signal Models 10^
6.3 Derivation ofthe Wiener Filter 106
6.4 Impulse ResponseTail Effect 107
6.5 Condition Number 108
6.6 Adaptive Algorithms 110
6.7 MIM0 Wiener Filter 116
6.8 Conclusions 119
References 120
7 Linear Prediction
J. Benesty, J. Chen, Y. Huang 121
7.1 Fundamentals 121
7.2 Forward Linear Prediction 122
7.3 Backward Linear Prediction 123
7.4 Levinson Durbin Algorithm 124
7.5 Lattice Predictor 126
7.6 Spectral Representation 127
7.7 Linear Interpolation 128
7.8 Line Spectrum Pair Representation 129
7.9 Multichannel Linear Prediction 130
7.10 Conclusions 133
References 133
8 The Kaiman Filter
S. Gannot, A. Yeredor 135
8.1 Derivation ofthe Kaiman Filter 136
8.2 Examples: Estimation of Parametric Stochastic Process
from Noisy Observations 141
8.3 Extensions ofthe Kaiman Filter 144
8.4 The Application ofthe Kaiman Filter to Speech Processing 149
8.5 Summary 157
References 157
9 Homomorphic Systems and Cepstrum Analysis of Speech
R.W. Schafer 161
9.1 Definitions 161
9.2 Z Transform Analysis 164
9.3 Discrete Time Model for Speech Production 165
9.4 The Cepstrum of Speech 166
9.5 Relation to LPC 169
9.6 Application to Pitch Detection 171
9.7 Applications to Analysis/Synthesis Coding 172
9.8 Applications to Speech Pattern Recognition 176
9.9 Summary 180
References 180
10 Pitch and Voicing Determination of Speech
with an Extension Toward Music Signals
W.J. Hess 181
10.1 Pitch in Time Variant Quasiperiodic Acoustic Signals 182
10.2 Short Term Analysis PDAs 185
10.3 Selected Time Domain Methods 192
10.4 A Short Look into Voicing Determination 195
10.5 Evaluation and Postprocessing 197
10.6 Applications in Speech and Music 201
10.7 Some New Challenges and Developments 203
10.8 Concluding Remarks 207
References 208
11 Formant Estimation and Tracking
D. O Shaughnessy 213
11.1 Historical 213
11.2 Vocal Tract Resonances 215
11.3 Speech Production 216
11.4 Acousticsofthe Vocal Tract 218
11.5 Short Time Speech Analysis 221
11.6 Formant Estimation 223
11.7 Summary 226
References 226
12 The STFT, Sinusoidal Models, and Speech Modification
M. M. Goodwin 229
12.1 The Short Time Fourier Transform 230
12.2 Sinusoidal Models 242
12.3 Speech Modification 253
References 256
13 Adaptive Blind Multichannel Identification
V. Huang, J. Benesty, J. Chen 259
13.1 Overview 259
13.2 Signal Model and Problem Formulation 260
13.3 Identifiability and Principle 261
13.4 Constrained Time Domain Multichannel LMS
and Newton Algorithms 262
13.5 Unconstrained Multichannel LMS Algorithm
with Optimal Step Size Control 266
13.6 Frequency Domain Blind Multichannel Identification Algorithms.... 268
13.7 Adaptive Multichannel Exponentiated Gradient Algorithm 276
13.8 Summary 279
References 279
Part C Speech Coding
14 Principles of Speech Coding
W.B. Kleijn 283
14.1 The Objective of Speech Coding 283
14.2 Speech Coder Attributes 284
14.3 A Universal Coder for Speech 286
14.4 Coding with Autoregressive Models 293
14.5 Distortion Measures and Coding Architecture 296
14.6 Summary 302
References 303
15 Voice over IP: Speech Transmission over Packet Networks
;. Skoglund, E. Kozica, J. Linden, R. Hagen, W. B. Kleijn 307
15.1 Voice Communication 307
15.2 Properties of the Network 308
15.3 Outline of a VolP System 313
15.4 Robust Encoding 317
15.5 Packet Loss Concealment 326
15.6 Conclusion 327
References 328
16 Low Bit Rate Speech Coding
k.M. McCree 331
16.1 Speech Coding 331
16.2 Fundamentals: Parametric Modeling of Speech Signals 332
16.3 Flexible Parametric Models 337
16.4 Efficient Quantization of Model Parameters 344
16.5 Low Rate Speech Coding Standards 345
16.6 Summary 347
References 347
17 Analysis by Synthesis Speech Coding
J. H. Chen, J. Thyssen 351
17.1 Overview 352
17.2 Basic Concepts of Analysis by Synthesis Coding 353
17.3 Overview of Prominent Analysis by Synthesis Speech Coders 357
17.4 Multipulse Linear Predictive Coding (MPLPC) 360
17.5 Regular Pulse Excitation with Long Term Prediction (RPE LTP) 362
17.6 The Original Code Excited Linear Prediction (CELP) Coder 363
17.7 US Federal Standard FS1016 CELP 367
17.8 Vector Sum Excited Linear Prediction (VSELP) 368
17.9 Low Delay CELP (LD CELP) 370
17.10 Pitch Synchronous Innovation CELP (PSI CELP) 371
17.11 Algebraic CELP (ACELP) 371
17.12 Conjugate Structure CELP (CS CELP) and CS ACELP 377
17.13 Relaxed CELP (RCELP) Generalized Analysis by Synthesis 378
17.14 eX CELP 381
17.15 iLBC 382
17.16 TSNFC 383
17.17 Embedded CELP 386
17.18 Summary of Analysis by Synthesis Speech Coders 388
17.19 Conclusion 390
References 390
18 Perceptual Audio Coding of Speech Signals
J. Herre, M. Lutzky 393
18.1 History of Audio Coding 393
18.2 Fundamentals of Perceptual Audio Coding 394
18.3 Some Successful Standardized Audio Coders 396
18.4 Perceptual Audio Coding for Real Time Communication 398
18.5 Hybrid/Crossover Coders 403
18.6 Summary 409
References 409
Part D Text to Speech Synthesis
19 Basic Principles of Speech Synthesis
J. Schroeter 413
19.1 The Basic Components of a TTS System 413
19.2 Speech Representations and Signal Processing
for Concatenative Synthesis 421
19.3 Speech Signal Transformation Principles 423
19.4 Speech Synthesis Evaluation 425
19.5 Conclusions 426
References 426
20 Rule Based Speech Synthesis
R. Carlson, B. Granström 429
20.1 Background 429
20.2 Terminal Analog 429
20.3 Controlling the Synthesizer 432
20.4 Special Applications of Rule Based Parametric Synthesis 434
20.5 Concluding Remarks 434
References 434
21 Corpus Based Speech Synthesis
T. Dutoit 437
21.1 Basics 437
21.2 Concatenative Synthesis with a Fixed Inventory 438
21.3 Unit Selection Based Synthesis ^7
21.4 Statistical Parametric Synthesis ^50
21.5 Conclusion ^53
References ^53
22 Linguistic Processing for Speech Synthesis
R. Sproat ^57
22.1 Why Linguistic Processing is Hard ^57
22.2 Fundamentals: Writing Systems and the Graphical Representation
of Language ^57
22.3 Problems to be Solved and Methods to Solve Them 458
22.4 Architectures for Multilingual Linguistic Processing 465
22.5 Document Level Processing ^65
22.6 Future Prospects ^66
References ^67
23 Prosodic Processing
J. van Santen, T. Mishra, E. Klabbers 471
23.1 Overview ^71
23.2 Historical Overview 475
23.3 Fundamental Challenges 476
23.4 A Survey of Current Approaches 477
23.5 Future Approaches 484
23.6 Conclusions 485
References 485
24 Voice Transformation
Y.Stylianou 489
24.1 Background 489
24.2 Source FilterTheory and Harmonie Models 490
24.3 Definitions 492
24.4 Source Modifications 494
24.5 Filter Modifications 498
24.6 Conversion Functions 499
24.7 Voice Conversion 500
24.8 Quality Issues in Voice Transformations 501
24.9 Summary 502
References 502
25 Expressive/Affective Speech Synthesis
N. Campbell 505
25.1 Overview 505
25.2 Characteristics of Affective Speech 506
25.3 The Communicative Functionality of Speech 508
25.4 Approaches to Synthesizing Expressive Speech 510
25.5 Modeling Human Speech 512
25.6 Conclusion 515
References 515
Part E Speech Recognition
26 Historical Perspective of the Field of ASR/NLU
L. Rabiner, B. H. Juang 521
26.1 ASR Methodologies 521
26.2 Important Milestones in Speech Recognition History 523
26.3 Generation 1 The Early History of Speech Recognition 524
26.4 Generation 2 The First Working Systems for Speech Recognition.... 524
26.5 Generation 3 The Pattern Recognition Approach
to Speech Recognition 525
26.6 Generation 4 The Era of the Statistical Model 530
26.7 Generation 5 The Future 534
26.8 Summary 534
References 535
27 HMMs and Related Speech Recognition Technologies
S. Young 539
27.1 Basic Framework 539
27.2 Architecture of an HMM Based Recognizer 540
27.3 HMM Based Acoustic Modeling 547
27.4 Normalization 550
27.5 Adaptation 551
27.6 Multipass Recognition Architectures 554
27.7 Conclusions 554
References 555
28 Speech Recognition with Weighted Finite State Transducers
M. Mohri, F. Pereira, M. Riley 559
28.1 Definitions 559
28.2 Overview 560
28.3 Algorithms 567
28.4 Applications to Speech Recognition 574
28.5 Conclusion 582
References 582
29 A Machine Learning Framework for Spoken Dialog Classification
C. Cortes, P. Haffner, M. Mohri 585
29.1 Motivation 585
29.2 Introduction to Kernel Methods 586
29.3 Rational Kernels 587
29.4 Algorithms 589
29.5 Experiments 591
29.6 Theoretical Results for Rational Kernels 593
29.7 Conclusion 5%
References 595
30 Towards Superhuman Speech Recognition
M. Picheny, D. Nahamoo 597
30.1 Current Status 597
30.2 A Multidomain Conversational Test Set 598
30.3 Listening Experiments 599
30.4 Recognition Experiments 601
30.5 Speculation 607
References 614
31 Natural Language Understanding
S. Roukos 617
31.1 Overview of NLU Applications 618
31.2 Natural Language Parsing 620
31.3 Practical Implementation 623
31.4 Speech Mining 623
31.5 Conclusion 625
References 626
32 Transcription and Distillation of Spontaneous Speech
S. Furui, T. Kawahara 627
32.1 Background 627
32.2 Overview of Research Activities on Spontaneous Speech 628
32.3 Analysis for Spontaneous Speech Recognition 632
32.4 Approaches to Spontaneous Speech Recognition 635
32.5 Metadata and Structure Extraction of Spontaneous Speech 640
32.6 Speech Summarization 644
32.7 Conclusions 647
References 647
33 Environmental Robustness
J. Droppo, A. Acero 653
33.1 Noise Robust Speech Recognition 653
33.2 Model Retraining and Adaptation 656
33.3 Feature Transformation and Normalization 657
33.4 A Model of the Environment 664
33.5 Structured Model Adaptation 667
33.6 Structured Feature Enhancement 671
33.7 Unifying Model and Feature Techniques 675
33.8 Conclusion 677
References 677
34 The Business of Speech Technologies
J. Wilpon, M. E. Gilbert, J. Cohen 681
34.1 Introduction 682
34.2 Network Based Speech Services 686
34.3 Device Based Speech Applications 692
34.4 Vision/Predications of Future Services Fueling the Trends 697
34.5 Conclusion 701
References 702
35 Spoken Dialogue Systems
V. Zue, S. Seneff 705
35.1 Technology Components and System Development 707
35.2 Development Issues 712
35.3 Historical Perspectives 714
35.4 New Directions 715
35.5 Concluding Remarks 718
References 718
Part F Speaker Recognition
36 Overview of Speaker Recognition
A.E. Rosenberg, F. Bimbot, S. Parthasarathy 725
36.1 Speaker Recognition 725
36.2 Measuring Speaker Features 729
36.3 Constructing Speaker Models 731
36.4 Adaptation 735
36.5 Decision and Performance 735
36.6 Selected Applications for Automatic Speaker Recognition 737
36.7 Summary 739
References 739
37 Text Dependent Speaker Recognition
M. Hebert 743
37.1 Brief Overview 743
37.2 Text Dependent Challenges 747
37.3 Selected Results 750
37.4 Concluding Remarks 760
References 760
38 Text Independent Speaker Recognition
D.A. Reynolds, W. M. Campbell 763
38.1 Introduction 763
38.2 Likelihood Ratio Detector 764
38.3 Features 766
38.4 Classifiers 767
38.5 Performance Assessment 776
38.6 Summary 778
References 779
Part G Language Recognition
39 Principles of Spoken Language Recognition
C. H. Lee 785
39.1 Spoken Language 785
39.2 Language Recognition Principles 786
39.3 Phone Recognition Followed by Language Modeling (PRLM) 788
39.4 Vector Space Characterization (VSC) 789
39.5 Spoken Language Verification 790
39.6 Discriminative Classifier Design 791
39.7 Summary 793
References 793
40 Spoken Language Characterization
M. P. Harper, M. Maxwell 797
40.1 Language versus Dialect 798
40.2 Spoken Language Collections 800
40.3 Spoken Language Characteristics 800
40.4 Human Language Identification 804
40.5 Text as a Source of Information on Spoken Languages 806
40.6 Summary 807
References 807
41 Automatic Language Recognition Via Spectral
and Token Based Approaches
D.A. Reynolds, l/l/. M. Campbell, W. Shen, E. Singer 811
41.1 Automatic Language Recognition 811
41.2 Spectral Based Methods 812
41.3 Token Based Methods 815
41.4 System Fusion 818
41.5 Performance Assessment 820
41.6 Summary 823
References 823
42 Vector Based Spoken Language Classification
H. Li, B. Ma, C. H. Lee 825
42.1 Vector Space Characterization 826
42.2 UnitSelection and Modeling 827
42.3 Front End: Voice Tokenization and Spoken Document Vectorization 830
42.4 Back End: Vector Based Classifier Design 831
42.5 Language Classification Experiments and Discussion 835
42.6 Summary 838
References 839
Part H Speech Enhancement
43 Fundamentals of Noise Reduction
J. Chen, J. Benesty, Y. Huang, E.J. Diethorn 843
43.1 Noise 843
43.2 Signal Model and Problem Formulation 845
43.3 Evaluation of Noise Reduction 846
43.4 Noise Reduction via FilteringTechniques 847
43.5 Noise Reduction via Spectral Restoration 857
43.6 Speech Model Based Noise Reduction 863
43.7 Summary 868
References 869
44 Spectral Enhancement Methods
/. Cohen, S. Gannot 873
44.1 Spectral Enhancement 874
44.2 Problem Formulation 875
44.3 Statistical Models 876
44.4 Signal Estimation 879
44.5 Signal Presence Probability Estimation 881
44.6 A Priori SNR Estimation 882
44.7 Noise Spectrum Estimation 888
44.8 Summary of a Spectral Enhancement Algorithm 891
44.9 Selection of Spectral Enhancement Algorithms 896
44.10 Conclusions 898
References 899
45 Adaptive Echo Cancelation for Voice Signals
M.M. Sondhi 903
45.1 Network Echoes 904
45.2 Single Channel Acoustic Echo Cancelation 915
45.3 MultiChannel Acoustic Echo Cancelation 921
45.4 Summary 925
References 926
46 Dereverberation
Y. Huang, J. Benesty, J. Chen 929
46.1 Background and Overview 929
46.2 Signal Model and Problem Formulation 931
46.3 Source Model Based Speech Dereverberation 932
46.4 Separation of Speech and Reverberation
via Homomorphic Transformation 936
46.5 Channel Inversion and Equalization 937
46.6 Summary 941
References 942
47 Adaptive Beamforming and Postfiltering
S. Gannot, I. Cohen 945
47.1 Problem Formulation 947
47.2 Adaptive Beamforming 948
47.3 Fixed Beamformer and Blocking Matrix 953
47.4 Identification of the Acoustical Transfer Function 955
47.5 Robustness and Distortion Weighting 960
47.6 MultiChannel Postfiltering 962
47.7 Performance Analysis 967
47.8 Experimental Results 972
47.9 Summary 972
47.A Appendix: Derivation of the Expected Noise Reduction
fora Coherent Noise Field 973
47.B Appendix: Equivalence Between Maximum SNR
and LCMV Beamformers 974
References 975
48 Feedback Control in Hearing Aids
A. Spriet, 5. Doclo, M. Moonen, J. Wouters 979
48.1 Problem Statement 980
48.2 Standard Adaptive Feedback Canceller 982
48.3 Feedback Cancellation Based on Prior Knowledge
of the Acoustic Feedback Path 986
48.4 Feedback Cancellation Based on Closed Loop System Identification. 990
48.5 Comparison 995
48.6 Conclusions 997
References 997
49 Active Noise Control
S.M. Kuo, D.R. Morgan 1001
49.1 Broadband Feedforward Active Noise Control 1002
49.2 Narrowband Feedforward Active Noise Control 1006
49.3 Feedback Active Noise Control 1010
49.4 MultiChannel ANC 1011
49.5 Summary 1015
References 1015
Part I Multichannel Speech Processing
50 Microphone Arrays
6. W. Elko, J. Meyer 1021
50.1 Microphone Array Beamforming 1021
50.2 Constant Beamwidth Microphone Array System 1029
50.3 Constrained Optimization of the Directional Gain 1030
50.4 Differential Microphone Arrays 1031
50.5 Eigenbeamforming Arrays 1034
50.6 Adaptive Array Systems 1037
50.7 Conclusions 1040
References 1040
51 Time Delay Estimation and Source Localization
Y. HuangJ. Benesty, J. Chen 1043
51.1 Technology Taxonomy 1043
51.2 Time Delay Estimation 1044
51.3 Source Localization 1054
51.4 Summary 1061
References 1062
52 Convolutive Blind Source Separation Methods
M.S. Pedersen, 1. Larsen, U. Kjems, L.C. Parra 1065
52.1 The Mixing Model 1066
52.2 The Separation Model 1068
52.3 Identification 1071
52.4 Separation Principle 1071
52.5 Time Versus Frequency Domain 1076
52.6 The Permutation Ambiguity 1078
52.7 Results 1084
52.8 Conclusion 1084
References 1084
53 Sound Field Reproduction
R. Rabenstein, S. Spors 1095
53.1 Sound Field Synthesis 1095
53.2 Mathematical Representation of Sound Fields 1096
53.3 Stereophony 1100
53.4 Vector Based Amplitude Panning 1103
53.5 Ambisonics 1104
53.6 Wave Field Synthesis 1109
References 1113
Acknowledgements 1115
About the Authors 1117
Detailed Contents 1133
Subject Index 1161
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| id | DE-604.BV022824540 |
| illustrated | Illustrated |
| indexdate | 2025-02-03T17:14:18Z |
| institution | BVB |
| isbn | 3540491252 9783540491255 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-016029844 |
| oclc_num | 612342075 |
| open_access_boolean | |
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| physical | XXXVI, 1176 S. Ill., graph. Darst. 1 DVD-ROM (12 cm) |
| publishDate | 2008 |
| publishDateSearch | 2008 |
| publishDateSort | 2008 |
| publisher | Springer |
| record_format | marc |
| series2 | Springer handbooks |
| spellingShingle | Springer handbook of speech processing with 113 tables Sprachverarbeitung (DE-588)4116579-2 gnd |
| subject_GND | (DE-588)4116579-2 (DE-588)4143413-4 |
| title | Springer handbook of speech processing with 113 tables |
| title_alt | Handbook of speech processing |
| title_auth | Springer handbook of speech processing with 113 tables |
| title_exact_search | Springer handbook of speech processing with 113 tables |
| title_full | Springer handbook of speech processing with 113 tables Jacob Benesty ... (eds.) |
| title_fullStr | Springer handbook of speech processing with 113 tables Jacob Benesty ... (eds.) |
| title_full_unstemmed | Springer handbook of speech processing with 113 tables Jacob Benesty ... (eds.) |
| title_short | Springer handbook of speech processing |
| title_sort | springer handbook of speech processing with 113 tables |
| title_sub | with 113 tables |
| topic | Sprachverarbeitung (DE-588)4116579-2 gnd |
| topic_facet | Sprachverarbeitung Aufsatzsammlung |
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