| Introduction | p. 1 |
| Noise Reduction in Speech Processing | p. 1 |
| The Paradigm for Noise Reduction | p. 6 |
| A Brief History of Noise Reduction Research | p. 7 |
| Organization of the Book | p. 10 |
| Some Notes to the Reader | p. 13 |
| Problem Formulation | p. 15 |
| In the Time Domain | p. 15 |
| In the Frequency Domain | p. 16 |
| In the Karhunen-Loeve Expansion (KLE) Domain | p. 18 |
| Summary | p. 20 |
| Performance Measures | p. 21 |
| Signal-to-Noise Ratio | p. 21 |
| Noise-Reduction Factor | p. 24 |
| Speech-Distortion Index | p. 25 |
| Speech-Reduction Factor | p. 27 |
| Discussion | p. 28 |
| Mean-Squared Error Criterion | p. 31 |
| In the Time Domain | p. 31 |
| In the Frequency Domain | p. 32 |
| In the KLE Domain | p. 34 |
| Summary | p. 36 |
| Pearson Correlation Coefficient | p. 37 |
| Correlation Coefficient Between Two Random Variables | p. 37 |
| Correlation Coefficient Between Two Random Vectors | p. 38 |
| Frequency-Domain Versions | p. 39 |
| KLE-Domain Versions | p. 39 |
| Summary | p. 40 |
| Fundamental Properties | p. 41 |
| In the Time Domain | p. 41 |
| In the Frequency Domain | p. 46 |
| In the KLE Domain | p. 50 |
| Summary | p. 57 |
| Optimal Filters in the Time Domain | p. 59 |
| Wiener Filter | p. 59 |
| Tradeoff Filters | p. 64 |
| Subspace Approach | p. 67 |
| Experiments | p. 68 |
| Experimental Setup | p. 68 |
| Effect of Forgetting Factor on Performance | p. 70 |
| Effect of Filter Length on Performance | p. 72 |
| Performance in Different Noise Conditions | p. 74 |
| Summary | p. 75 |
| Optimal Filters in the Frequency Domain | p. 77 |
| Wiener Filter | p. 77 |
| Parametric Wiener Filter | p. 81 |
| Tradeoff Filter | p. 82 |
| Experiments | p. 86 |
| Impact of Input SNR on Filter Gain and Speech Distortion | p. 86 |
| Noise Estimation | p. 86 |
| Performance Comparison in NYSE Noise | p. 89 |
| Performance Comparison in Car Noise | p. 93 |
| Summary | p. 94 |
| Optimal Filters in the KLE Domain | p. 95 |
| Class I | p. 95 |
| Wiener Filter | p. 95 |
| Parametric Wiener Filter | p. 100 |
| Tradeoff Filter | p. 101 |
| Class II | p. 105 |
| Wiener Filter | p. 105 |
| Tradeoff Filter | p. 108 |
| Experiments | p. 111 |
| Impact of Forgetting Factor on Performance of Class-I Filters | p. 111 |
| Effect of Filter Length on Performance of Class-I Filters | p. 113 |
| Estimation of Clean Speech Correlation Matrix | p. 114 |
| Performance of Class-I Filters in Different Noise Conditions | p. 116 |
| Impact of Forgetting Factor on Performance of Class-II Filters | p. 116 |
| Effect of Filter Length on Performance of Class-II Filters | p. 120 |
| Summary | p. 121 |
| Optimal Filters in the Transform Domain | p. 123 |
| Generalization of the KLE | p. 123 |
| Performance Measures | p. 127 |
| SNR | p. 127 |
| Noise-Reduction Factor | p. 128 |
| Speech-Distortion Index | p. 129 |
| Speech-Reduction Factor | p. 130 |
| MSE Criterion | p. 131 |
| PCC and Fundamental Properties | p. 132 |
| Examples of Filter Design | p. 138 |
| Wiener Filter | p. 138 |
| Parametric Wiener Filter | p. 142 |
| Tradeoff Filter | p. 143 |
| Examples of Unitary Matrices | p. 145 |
| Experiments | p. 146 |
| Performance of Wiener Filter in White Gaussian Noise | p. 146 |
| Effect of Filter Length on Performance | p. 148 |
| Performance of Tradeoff Filter in White Gaussian Noise | p. 148 |
| Summary | p. 152 |
| Spectral Enhancement Methods | p. 153 |
| Problem Formulation | p. 153 |
| Performance Measures | p. 155 |
| SNR | p. 155 |
| Noise-Reduction Factor | p. 156 |
| Speech-Distortion Index | p. 157 |
| Speech-Reduction Factor | p. 158 |
| MSE Criterion | p. 159 |
| Signal Model | p. 161 |
| Signal Estimation | p. 162 |
| MMSE Spectral Estimation | p. 162 |
| MMSE Spectral Amplitude Estimation | p. 163 |
| MMSE Log-Spectral Amplitude Estimation | p. 164 |
| Spectral Variance Model | p. 166 |
| GARCH Model | p. 166 |
| Modeling Speech Spectral Variance | p. 168 |
| Model Estimation | p. 169 |
| Spectral Variance Estimation | p. 170 |
| Relation to Decision-Directed Estimation | p. 172 |
| Summary of Spectral Enhancement Algorithm | p. 174 |
| Experimental Results | p. 176 |
| Summary | p. 181 |
| A Practical Example: Multichannel Noise Reduction for Voice Communication in Spacesuits | p. 183 |
| Problem Description | p. 183 |
| Problem Analysis | p. 186 |
| Sources of Noise in Spacesuits | p. 186 |
| Noise Cancelling Microphones | p. 188 |
| Suggested Algorithms | p. 192 |
| Nearfield, Wideband Microphone Array Beamforming for Speech Acquisition in Spacesuits | p. 193 |
| Multichannel Noise Reduction: a More Practical Microphone Array Signal Processing Technique | p. 200 |
| Single-Channel Noise Reduction | p. 201 |
| Adaptive Noise Cancellation | p. 202 |
| Algorithm Validation | p. 203 |
| In-Helmet Multichannel Acoustic Data Collection | p. 203 |
| Performance Evaluation of Beamforming Algorithms | p. 208 |
| Validation of Multichannel Noise Reduction Algorithms | p. 214 |
| Validation of Single-Channel Noise Reduction Algorithms | p. 214 |
| Feasibility Assessment of Using Adaptive Noise Cancellation in Spacesuits | p. 214 |
| Summary | p. 217 |
| References | p. 219 |
| Index | p. 227 |
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