Multimedia Signal Processing: Theory and Applications in Speech, Music and Communications

0470062010......Page 1
Contents......Page 10
Preface......Page 16
Acknowledgement......Page 20
Symbols......Page 22
Abbreviations......Page 26
Part I Basic Digital Signal Processing......Page 30
1.1 Signals and Information......Page 32
1.2 Signal Processing Methods......Page 34
1.3 Applications of Digital Signal Processing......Page 37
1.4 Summary......Page 52
2.1 Introduction......Page 54
2.2 Fourier Series: Representation of Periodic Signals......Page 56
2.3 Fourier Transform: Representation of Nonperiodic Signals......Page 62
2.4 Discrete Fourier Transform......Page 77
2.5 Short-Time Fourier Transform......Page 86
2.6 Fast Fourier Transform (FFT)......Page 88
2.7 2-D Discrete Fourier Transform (2-D DFT)......Page 94
2.8 Discrete Cosine Transform (DCT)......Page 95
2.9 Some Applications of the Fourier Transform......Page 97
2.10 Summary......Page 103
3.1 Introduction......Page 108
3.2 Derivation of the z-Transform......Page 110
3.3 The z-Plane and the Unit Circle......Page 112
3.4 Properties of z-Transform......Page 117
3.5 z-Transfer Function, Poles (Resonance) and Zeros (Anti-resonance)......Page 120
3.6 z-Transform of Analysis of Exponential Transient Signals......Page 129
3.7 Inverse z-Transform......Page 133
3.8 Summary......Page 135
4.1 Introduction......Page 140
4.2 Linear Time-Invariant Digital Filters......Page 142
4.3 Recursive and Non-Recursive Filters......Page 144
4.4 Filtering Operation: Sum of Vector Products, A Comparison of Convolution and Correlation......Page 146
4.5 Filter Structures: Direct, Cascade and Parallel Forms......Page 148
4.6 Linear Phase FIR Filters......Page 151
4.7 Design of Digital FIR Filter-banks......Page 165
4.8 Quadrature Mirror Sub-band Filters......Page 168
4.9 Design of Infinite Impulse Response (IIR) Filters by Pole–zero Placements......Page 174
4.11 Summary......Page 177
5.1 Introduction......Page 184
5.2 Sampling a Continuous-Time Signal......Page 187
5.3 Quantisation......Page 191
5.4 Sampling Rate Conversion: Interpolation and Decimation......Page 195
5.5 Summary......Page 200
Part II Model-Based Signal Processing......Page 202
6 Information Theory and Probability Models......Page 204
6.1 Introduction: Probability and Information Models......Page 205
6.2 Random Processes......Page 206
6.3 Probability Models of Random Signals......Page 211
6.4 Information Models......Page 218
6.5 Stationary and Non-Stationary Random Processes......Page 228
6.6 Statistics (Expected Values) of a Random Process......Page 231
6.7 Some Useful Practical Classes of Random Processes......Page 241
6.8 Transformation of a Random Process......Page 254
6.9 Search Engines: Citation Ranking......Page 259
6.10 Summary......Page 260
7.1 Bayesian Estimation Theory: Basic Definitions......Page 262
7.2 Bayesian Estimation......Page 271
7.3 Expectation Maximisation Method......Page 284
7.4 Cramer–Rao Bound on the Minimum Estimator Variance......Page 286
7.5 Design of Gaussian Mixture Models (GMM)......Page 289
7.6 Bayesian Classification......Page 292
7.7 Modelling the Space of a Random Process......Page 299
7.8 Summary......Page 302
8.1 Least Square Error Estimation: Wiener–Kolmogorov Filter......Page 304
8.2 Block-Data Formulation of the Wiener Filter......Page 309
8.3 Interpretation of Wiener Filter as Projection in Vector Space......Page 311
8.4 Analysis of the Least Mean Square Error Signal......Page 313
8.5 Formulation of Wiener Filters in the Frequency Domain......Page 314
8.6 Some Applications of Wiener Filters......Page 315
8.7 Implementation of Wiener Filters......Page 321
8.8 Summary......Page 323
9.1 Introduction......Page 326
9.2 State-Space Kalman Filters......Page 328
9.3 Sample Adaptive Filters......Page 336
9.4 Recursive Least Square (RLS) Adaptive Filters......Page 338
9.5 The Steepest-Descent Method......Page 342
9.6 LMS Filter......Page 346
9.7 Summary......Page 350
10.1 Linear Prediction Coding......Page 352
10.2 Forward, Backward and Lattice Predictors......Page 361
10.3 Short-Term and Long-Term Predictors......Page 368
10.4 MAP Estimation of Predictor Coefficients......Page 370
10.5 Formant-Tracking LP Models......Page 372
10.6 Sub-Band Linear Prediction Model......Page 373
10.7 Signal Restoration Using Linear Prediction Models......Page 374
10.8 Summary......Page 379
11.1 Statistical Models for Non-Stationary Processes......Page 382
11.2 Hidden Markov Models......Page 384
11.3 Training Hidden Markov Models......Page 390
11.4 Decoding Signals Using Hidden Markov Models......Page 396
11.5 HMM in DNA and Protein Sequences......Page 400
11.6 HMMs for Modelling Speech and Noise......Page 401
11.7 Summary......Page 407
12 Eigenvector Analysis, Principal Component Analysis and Independent Component Analysis......Page 410
12.1 Introduction – Linear Systems and Eigenanalysis......Page 411
12.2 Eigenvectors and Eigenvalues......Page 415
12.3 Principal Component Analysis (PCA)......Page 418
12.4 Independent Component Analysis......Page 422
12.5 Summary......Page 441
Part III Applications of Digital Signal Processing to Speech, Music and Telecommunications......Page 444
13 Music Signal Processing and Auditory Perception......Page 446
13.2 Musical Notes, Intervals and Scales......Page 447
13.3 Musical Instruments......Page 455
13.4 Review of Basic Physics of Sounds......Page 468
13.5 Music Signal Features and Models......Page 476
13.6 Anatomy of the Ear and the Hearing Process......Page 480
13.7 Psychoacoustics of Hearing......Page 491
13.8 Music Coding (Compression)......Page 500
13.9 High Quality Audio Coding: MPEG Audio Layer-3 (MP3)......Page 504
13.10 Stereo Music Coding......Page 507
13.11 Summary......Page 509
14.1 Speech Communication......Page 512
14.2 Acoustic Theory of Speech: The Source-filter Model......Page 513
14.3 Speech Models and Features......Page 519
14.4 Linear Prediction Models of Speech......Page 520
14.5 Harmonic Plus Noise Model of Speech......Page 521
14.6 Fundamental Frequency (Pitch) Information......Page 525
14.7 Speech Coding......Page 529
14.8 Speech Recognition......Page 539
14.9 Summary......Page 554
15 Speech Enhancement......Page 556
15.2 Single-Input Speech Enhancement Methods......Page 557
15.3 Speech Bandwidth Extension – Spectral Extrapolation......Page 576
15.4 Interpolation of Lost Speech Segments – Packet Loss Concealment......Page 582
15.5 Multi-Input Speech Enhancement Methods......Page 591
15.6 Speech Distortion Measurements......Page 594
15.7 Summary......Page 598
16.1 Introduction: Acoustic and Hybrid Echo......Page 602
16.2 Telephone Line Hybrid Echo......Page 604
16.3 Hybrid (Telephone Line) Echo Suppression......Page 606
16.4 Adaptive Echo Cancellation......Page 607
16.5 Acoustic Echo......Page 610
16.6 Sub-Band Acoustic Echo Cancellation......Page 613
16.7 Echo Cancellation with Linear Prediction Pre-whitening......Page 614
16.8 Multi-Input Multi-Output Echo Cancellation......Page 615
16.9 Summary......Page 618
17.1 Introduction......Page 620
17.2 Blind Equalisation Using Channel Input Power Spectrum......Page 627
17.3 Equalisation Based on Linear Prediction Models......Page 630
17.4 Bayesian Blind Deconvolution and Equalisation......Page 632
17.5 Blind Equalisation for Digital Communication Channels......Page 640
17.6 Equalisation Based on Higher-Order Statistics......Page 645
17.7 Summary......Page 652
18.1 Introduction to Cellular Communication......Page 654
18.2 Communication Signal Processing in Mobile Systems......Page 660
18.3 Capacity, Noise, and Spectral Efficiency......Page 661
18.4 Multi-path and Fading in Mobile Communication......Page 663
18.5 Smart Antennas – Space–Time Signal Processing......Page 668
18.6 Summary......Page 671
Index......Page 672