Speech Enhancement

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 "...

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Bibliographic Details
Main Authors: Benesty, Jacob (Author), Makino, Shoji (Author), Chen, Jingdong (Author)
Corporate Author: SpringerLink (Online service)
Format: Electronic eBook
Language:English
Published: Berlin, Heidelberg : Springer Berlin Heidelberg, 2005.
Series:Signals and Communication Technology
Subjects:
Online Access:Full Text via HEAL-Link
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 Stochastic 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.