Jacob Benesty – författare

Speech enhancement is a classical problem in signal processing, yet still largely unsolved. Two of the conventional approaches for solving this problem are linear filtering, like the classical Wiener filter, and subspace methods. These approaches have traditionally been treated as different classes of methods and have been introduced in somewhat different contexts. Linear filtering methods originate in stochastic processes, while subspace methods have largely been based on developments in numerical linear algebra and matrix approximation theory.

This book bridges the gap between these two classes of methods by showing how the ideas behind subspace methods can be incorporated into traditional linear filtering. In the context of subspace methods, the enhancement problem can then be seen as a classical linear filter design problem. This means that various solutions can more easily be compared and their performance bounded and assessed in terms of noise reduction and speech distortion. The book shows how various filter designs can be obtained in this framework, including the maximum SNR, Wiener, LCMV, and MVDR filters, and how these can be applied in various contexts, like in single-channel and multichannel speech enhancement, and in both the time and frequency domains.

Presents a unified framework of far-field and near-field array techniques for noise source identification and sound field visualization, from theory to application.

Acoustic Array Systems: Theory, Implementation, and Application provides an overview of microphone array technology with applications in noise source identification and sound field visualization. In the comprehensive treatment of microphone arrays, the topics covered include an introduction to the theory, far-field and near-field array signal processing algorithms, practical implementations, and common applications: vehicles, computing and communications equipment, compressors, fans, and household appliances, and hands-free speech. The author concludes with other emerging techniques and innovative algorithms.

A valuable resource for Postgraduates and researchers in acoustics, noise control engineering, audio engineering, and signal processing.

Presents a unified framework of far-field and near-field array techniques for noise source identification and sound field visualization, from theory to application.

Acoustic Array Systems: Theory, Implementation, and Application provides an overview of microphone array technology with applications in noise source identification and sound field visualization. In the comprehensive treatment of microphone arrays, the topics covered include an introduction to the theory, far-field and near-field array signal processing algorithms, practical implementations, and common applications: vehicles, computing and communications equipment, compressors, fans, and household appliances, and hands-free speech. The author concludes with other emerging techniques and innovative algorithms.

A valuable resource for Postgraduates and researchers in acoustics, noise control engineering, audio engineering, and signal processing.

A comprehensive guide to the theory and practice of signal enhancement and array signal processing, including matlab codes, exercises and instructor and solution manuals  

A comprehensive guide to the theory and practice of signal enhancement and array signal processing, including matlab codes, exercises and instructor and solution manuals  

The focus of this book is on array processing and beamforming with Kronecker products. It considers a large family of sensor arrays that allow the steering vector to be decomposed as a Kronecker product of two steering vectors of smaller virtual arrays. Instead of directly designing a global beamformer for the original array, once the steering vector has been decomposed, smaller virtual beamformers are designed and separately optimized for each virtual array. This means the matrices that need to be inverted are smaller, which increases the robustness of the beamformers, and reduces the size of the observations.

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.