Speech Enhancement

by Jacob Benesty (Editor), Shoji Makino (Editor), Jingdong Chen (Editor)

Overview

We live in a noisy world! In all applications (telecommunications, hands-free communications, recording, human-machine interfaces, etc.) that require at least one microphone, the signal of interest is usually contaminated by noise and reverberation. As a result, the microphone signal has to be "cleaned" with digital signal processing tools before it is played out, transmitted, or stored.

This book is about speech enhancement. Different well-known and state-of-the-art methods for noise reduction, with one or multiple microphones, are discussed. By speech enhancement, we mean not only noise reduction but also dereverberation and separation of independent signals. These topics are also covered in this book. However, the general emphasis is on noise reduction because of the large number of applications that can benefit from this technology.

The goal of this book is to provide a strong reference for researchers, engineers, and graduate students who are interested in the problem of signal and speech enhancement. To do so, we invited well-known experts to contribute chapters covering the state of the art in this focused field.

Product Details

ISBN-13:	9783642063176
Publisher:	Springer Berlin Heidelberg
Publication date:	12/15/2010
Series:	Signals and Communication Technology
Edition description:	Softcover reprint of hardcover 1st ed. 2005
Pages:	406
Product dimensions:	6.10(w) x 9.25(h) x 0.36(d)

Table of Contents

Study of the Wiener Filter for Noise Reduction.- Statistical Methods for the Enhancement of Noisy Speech.- Single- and Multi-Microphone Spectral Amplitude Estimation Using a Super-Gaussian Speech Model.- From Volatility Modeling of Financial Time-Series to Shastic Modeling and Enhancement of Speech Signals.- Single-Microphone Noise Suppression for 3G Handsets Based on Weighted Noise Estimation.- Signal Subspace Techniques for Speech Enhancement.- Speech Enhancement: Application of the Kalman Filter in the Estimate-Maximize (EM) Framework.- Speech Distortion Weighted Multichannel Wiener Filtering Techniques for Noise Reduction.- Adaptive Microphone Array Employing Spatial Quadratic Soft Constraints and Spectral Shaping.- Single-Microphone Blind Dereverberation.- Separation and Dereverberation of Speech Signals with Multiple Microphones.- Frequency-Domain Blind Source Separation.- Subband Based Blind Source Separation.- Real-Time Blind Source Separation for Moving Speech Signals.- Separation of Speech by Computational Auditory Scene Analysis.