Microphone Arrays

✍ Scribed by Jacob Benesty; Gongping Huang; Jingdong Chen; Ningning Pan

• Publisher: Springer Nature
• Year: 2023
• Tongue: English
• Leaves: 232
• Category: Library

✦ Synopsis

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.

✦ Table of Contents

Preface
Contents
1 Introduction
1.1 Sound Signal Acquisition and Processing
1.2 Microphone Arrays and Their Applications
1.2.1 Airborne Dipping and Reconfigurable Microphone Arrays
1.2.2 Linear Microphone Arrays for Smart Panels
1.3 Major Addressed Problems
1.4 Organization of the Work
References
2 Limitations of Single Microphone Processing
2.1 Signal Model
2.2 Optimal Noise Reduction
2.3 Importance of Spatial Information
2.4 Illustrative Examples
References
3 Fundamentals of Microphone Array Processing
3.1 Signal Model
3.2 Beamforming
3.3 Performance Measures
3.4 Examples of Conventional Beamformers
3.5 Input SNR Estimation
3.6 Comparison of Different Array Geometries
3.7 Illustrative Examples
References
4 Principal Component Analysis in Noise Reduction and Beamforming
4.1 Brief Overview of PCA
4.2 PCA for White Noise Reduction
4.3 Noise-Dependent PCA for General Noise Reduction
4.4 Applications to Beamforming
4.5 Illustrative Examples
References
5 Low-Rank Beamforming
5.1 Fundamental Concepts
5.2 Signal Model and Beamforming
5.3 Performance Measures
5.4 Optimal Beamformers
5.5 Illustrative Examples
References
6 Distortionless Beamforming
6.1 Signal Model, Performance Measures, and Distortionless Beamformers
6.2 Principle of Distortionless Beamforming
6.3 Robust Beamforming
6.4 Another Perspective
6.5 Illustrative Examples
References
7 Differential Beamforming
7.1 Signal Model
7.2 First-Order Differential Beamforming
7.3 Higher-Order Differential Beamforming
7.4 Illustrative Examples
References
8 Adaptive Noise Cancellation
8.1 Signal Model
8.2 Arrangement of a Noise Reference
8.3 Noise Cancellation
8.4 Low-Rank Noise Cancellation
8.5 Illustrative Examples
References
9 Binaural Beamforming
9.1 Signal Model
9.2 Motivation
9.3 Binaural Beamforming and Performance Measures
9.4 Examples of Binaural Beamformers
9.5 Illustrative Examples
9.5.1 Objective Measurements
9.5.2 Listening Tests
References
10 Large Array Beamforming
10.1 Basic Concepts and Signal Model
10.2 Beamforming
10.3 Performance Measures
10.4 Examples of Optimal Beamformers
10.5 Illustrative Examples
References
Index