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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Online Access: | http://dx.doi.org/10.1155/S1110865703305050 |
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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 |
work_keys_str_mv |
AT gannotsharon anintegratedrealtimebeamformingandpostfilteringsystemfornonstationarynoiseenvironments AT berdugobaruch anintegratedrealtimebeamformingandpostfilteringsystemfornonstationarynoiseenvironments AT cohenisrael anintegratedrealtimebeamformingandpostfilteringsystemfornonstationarynoiseenvironments AT gannotsharon integratedrealtimebeamformingandpostfilteringsystemfornonstationarynoiseenvironments AT berdugobaruch integratedrealtimebeamformingandpostfilteringsystemfornonstationarynoiseenvironments AT cohenisrael integratedrealtimebeamformingandpostfilteringsystemfornonstationarynoiseenvironments |
_version_ |
1725791066661060608 |