Microphone Arrays

This book explains the motivation for using microphone arrays as opposed to using a single sensor for sound acquisition. The book then goes on to summarize the most useful ideas, concepts, results, and new algorithms therein. The material presented in this work includes analysis of the advantages of using microphone arrays, including dimensionality reduction to remove the redundancy while preserving the variability of the array signals using the principal component analysis (PCA). The authors also discuss benefits such as beamforming with low-rank approximations, fixed, adaptive, and robust distortionless beamforming, differential beamforming, and a new form of binaural beamforming that takes advantage of both beamforming and human binaural hearing properties to improve speech intelligibility. The book makes the microphone array signal processing theory and applications available in a complete and self-contained text. The authors attempt to explain the main ideas in a clear and rigorous way so that the reader can easily capture the potentials, opportunities, challenges, and limitations of microphone array signal processing. This book is written for those who work on the topics of microphone arrays, noise reduction, speech enhancement, speech communication, and human-machine speech interfaces. Preface 6 Contents 8 1 Introduction 11 1.1 Sound Signal Acquisition and Processing 11 1.2 Microphone Arrays and Their Applications 13 1.2.1 Airborne Dipping and Reconfigurable Microphone Arrays 14 1.2.2 Linear Microphone Arrays for Smart Panels 16 1.3 Major Addressed Problems 17 1.4 Organization of the Work 18 References 20 2 Limitations of Single Microphone Processing 22 2.1 Signal Model 22 2.2 Optimal Noise Reduction 23 2.3 Importance of Spatial Information 25 2.4 Illustrative Examples 28 References 33 3 Fundamentals of Microphone Array Processing 34 3.1 Signal Model 34 3.2 Beamforming 36 3.3 Performance Measures 37 3.4 Examples of Conventional Beamformers 40 3.5 Input SNR Estimation 44 3.6 Comparison of Different Array Geometries 45 3.7 Illustrative Examples 48 References 65 4 Principal Component Analysis in Noise Reduction and Beamforming 66 4.1 Brief Overview of PCA 66 4.2 PCA for White Noise Reduction 69 4.3 Noise-Dependent PCA for General Noise Reduction 73 4.4 Applications to Beamforming 79 4.5 Illustrative Examples 82 References 94 5 Low-Rank Beamforming 95 5.1 Fundamental Concepts 95 5.2 Signal Model and Beamforming 99 5.3 Performance Measures 100 5.4 Optimal Beamformers 102 5.5 Illustrative Examples 106 References 119 6 Distortionless Beamforming 120 6.1 Signal Model, Performance Measures, and Distortionless Beamformers 120 6.2 Principle of Distortionless Beamforming 122 6.3 Robust Beamforming 126 6.4 Another Perspective 129 6.5 Illustrative Examples 135 References 145 7 Differential Beamforming 146 7.1 Signal Model 146 7.2 First-Order Differential Beamforming 147 7.3 Higher-Order Differential Beamforming 158 7.4 Illustrative Examples 160 References 174 8 Adaptive Noise Cancellation 175 8.1 Signal Model 175 8.2 Arrangement of a Noise Reference 176 8.3 Noise Cancellation 177 8.4 Low-Rank Noise Cancellation 179 8.5 Illustrative Examples 181 References 187 9 Binaural Beamforming 188 9.1 Signal Model 188 9.2 Motivation 190 9.3 Binaural Beamforming and Performance Measures 190 9.4 Examples of Binaural Beamformers 194 9.5 Illustrative Examples 198 9.5.1 Objective Measurements 198 9.5.2 Listening Tests 206 References 208 10 Large Array Beamforming 210 10.1 Basic Concepts and Signal Model 210 10.2 Beamforming 212 10.3 Performance Measures 215 10.4 Examples of Optimal Beamformers 217 10.5 Illustrative Examples 219 References 228 Index 229