An Integrated Real-Time Beamforming and Postfiltering System for Nonstationary Noise Environments

<p/> <p>We present a novel approach for real-time multichannel speech enhancement in environments of nonstationary noise and time-varying acoustical transfer functions (ATFs). The proposed system integrates adaptive beamforming, ATF identification, soft signal detection, and multichannel...

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Main Authors: Gannot Sharon, Berdugo Baruch, Cohen Israel
Format: Article
Language:English
Published: SpringerOpen 2003-01-01
Series:EURASIP Journal on Advances in Signal Processing
Subjects:
Online Access:http://dx.doi.org/10.1155/S1110865703305050
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spelling doaj-075e511ba927427ca8dbbbb99582696f2020-11-24T22:16:08ZengSpringerOpenEURASIP Journal on Advances in Signal Processing1687-61721687-61802003-01-01200311936861An Integrated Real-Time Beamforming and Postfiltering System for Nonstationary Noise EnvironmentsGannot SharonBerdugo BaruchCohen Israel<p/> <p>We present a novel approach for real-time multichannel speech enhancement in environments of nonstationary noise and time-varying acoustical transfer functions (ATFs). The proposed system integrates adaptive beamforming, ATF identification, soft signal detection, and multichannel postfiltering. The noise canceller branch of the beamformer and the ATF identification are adaptively updated online, based on hypothesis test results. The noise canceller is updated only during stationary noise frames, and the ATF identification is carried out only when desired source components have been detected. The hypothesis testing is based on the nonstationarity of the signals and the transient power ratio between the beamformer primary output and its reference noise signals. Following the beamforming and the hypothesis testing, estimates for the signal presence probability and for the noise power spectral density are derived. Subsequently, an optimal spectral gain function that minimizes the mean square error of the log-spectral amplitude (LSA) is applied. Experimental results demonstrate the usefulness of the proposed system in nonstationary noise environments.</p>http://dx.doi.org/10.1155/S1110865703305050array signal processingsignal detectionacoustic noise measurementspeech enhancementspectral analysisadaptive signal processing
collection DOAJ
language English
format Article
sources DOAJ
author Gannot Sharon
Berdugo Baruch
Cohen Israel
spellingShingle Gannot Sharon
Berdugo Baruch
Cohen Israel
An Integrated Real-Time Beamforming and Postfiltering System for Nonstationary Noise Environments
EURASIP Journal on Advances in Signal Processing
array signal processing
signal detection
acoustic noise measurement
speech enhancement
spectral analysis
adaptive signal processing
author_facet Gannot Sharon
Berdugo Baruch
Cohen Israel
author_sort Gannot Sharon
title An Integrated Real-Time Beamforming and Postfiltering System for Nonstationary Noise Environments
title_short An Integrated Real-Time Beamforming and Postfiltering System for Nonstationary Noise Environments
title_full An Integrated Real-Time Beamforming and Postfiltering System for Nonstationary Noise Environments
title_fullStr An Integrated Real-Time Beamforming and Postfiltering System for Nonstationary Noise Environments
title_full_unstemmed An Integrated Real-Time Beamforming and Postfiltering System for Nonstationary Noise Environments
title_sort integrated real-time beamforming and postfiltering system for nonstationary noise environments
publisher SpringerOpen
series EURASIP Journal on Advances in Signal Processing
issn 1687-6172
1687-6180
publishDate 2003-01-01
description <p/> <p>We present a novel approach for real-time multichannel speech enhancement in environments of nonstationary noise and time-varying acoustical transfer functions (ATFs). The proposed system integrates adaptive beamforming, ATF identification, soft signal detection, and multichannel postfiltering. The noise canceller branch of the beamformer and the ATF identification are adaptively updated online, based on hypothesis test results. The noise canceller is updated only during stationary noise frames, and the ATF identification is carried out only when desired source components have been detected. The hypothesis testing is based on the nonstationarity of the signals and the transient power ratio between the beamformer primary output and its reference noise signals. Following the beamforming and the hypothesis testing, estimates for the signal presence probability and for the noise power spectral density are derived. Subsequently, an optimal spectral gain function that minimizes the mean square error of the log-spectral amplitude (LSA) is applied. Experimental results demonstrate the usefulness of the proposed system in nonstationary noise environments.</p>
topic array signal processing
signal detection
acoustic noise measurement
speech enhancement
spectral analysis
adaptive signal processing
url http://dx.doi.org/10.1155/S1110865703305050
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