Bücher von Jingdong Chen

This book is devoted to the study of the problem of speech enhancement whose objective is the recovery of a signal of interest (i.e., speech) from noisy observations. Typically, the recovery process is accomplished by passing the noisy observations through a linear filter (or a linear transformation). Since both the desired speech and undesired noise are filtered at the same time, the most critical issue of speech enhancement resides in how to design a proper optimal filter that can fully take advantage of the difference between the speech and noise statistics to mitigate the noise effect as much as possible while maintaining the speech perception identical to its original form. The optimal filters can be designed either in the time domain or in a transform space. As the title indicates, this book will focus on developing and analyzing optimal filters in the Karhunen-Loeve expansion (KLE) domain. We begin by describing the basic problem of speech enhancement and the fundamental principles to solve it in the time domain. We then explain how the problem can be equivalently formulated in the KLE domain. Next, we divide the general problem in the KLE domain into four groups, depending on whether interframe and interband information is accounted for, leading to four linear models for speech enhancement in the KLE domain. For each model, we introduce signal processing measures to quantify the performance of speech enhancement, discuss the formation of different cost functions, and address the optimization of these cost functions for the derivation of different optimal filters. Both theoretical analysis and experiments will be provided to study the performance of these filters and the links between the KLE-domain and time-domain optimal filters will be examined. Table of Contents: Introduction / Problem Formulation / Optimal Filters in the Time Domain / Linear Models for Signal Enhancement in the KLE Domain / Optimal Filters in the KLE Domain with Model 1 / Optimal Filters in the KLE Domain with Model 2 / Optimal Filters in the KLE Domain with Model 3 / Optimal Filters in the KLE Domain with Model 4 / Experimental Study

This book provides a systematic study of the fundamental theory and methods of beamforming with differential microphone arrays (DMAs), or differential beamforming in short.

Though noise reduction and speech enhancement problems have been studied for at least five decades, advances in our understanding and the development of reliable algorithms are more important than ever, as they support the design of tailored solutions for clearly defined applications.

The main objective of this concise book is to derive and explain the most fundamental algorithms from a strictly broadband (signals and/or processing) viewpoint. Thanks to the approach taken here, new concepts come to light that have great potential.

We divide the general problem into five basic categories depending on the number of microphones being used and whether the interframe or interband correlation is considered.

Additive noise is ubiquitous in acoustics environments and can affect the intelligibility and quality of speech signals. Therefore, a so-called noise reduction algorithm is required to mitigate the effect of the noise that is picked up by the microphones.

The systematic coverage of differential microphone arrays in this book approaches the topic from a signal processing perspective, developing fundamental theory and algorithms and analyzing the relative performance, and limitations, of varied classes of DMA.

This text offers an overview of the state-of-the-art of noise reduction algorithms, focusing on the most useful techniques. In addition, it rigorously derives these techniques and proves many fundamental and intuitive results often taken for granted.

This book reviews acoustic MIMO scenarios for improving human-machine interaction. The book establishes an acoustic MIMO paradigm, linking MIMO signal processing with classical signal processing. Also presented is a novel analysis of acoustic applications to reinforce the fundamentals of acoustic MIMO signal processing.