Improved a priori SNR estimation with application in Log-MMSE speech estimation

A speech enhancement method utilizing the harmonic structure of speech is presented. The method is an extension of the well known minimum mean square error log-spectral amplitude estimator(Log MMSE) method for speech enhancement. The improvement lies specifically on a priori SNR estimation by utiliz...

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Main Authors: Höglund, N., Nordholm, Sven
Format: Conference Paper
Published: 2009
Online Access:http://hdl.handle.net/20.500.11937/8105
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author Höglund, N.
Nordholm, Sven
author_facet Höglund, N.
Nordholm, Sven
author_sort Höglund, N.
building Curtin Institutional Repository
collection Online Access
description A speech enhancement method utilizing the harmonic structure of speech is presented. The method is an extension of the well known minimum mean square error log-spectral amplitude estimator(Log MMSE) method for speech enhancement. The improvement lies specifically on a priori SNR estimation by utilizing harmonic structure of speech. The method is based on a conditional averaging operation over adjacent frequency bands for each processed data block. The actual frequency bands used in the conditional averaging is determined by a pitch detector. Thus voiced segments are averaged over frequency according to the pitch and the corresponding harmonic structure of voiced speech. Non-voiced segments are averaged over frequency according to a random number depending on the pitch value. The result is overall better SNR and SNRSeg values in white noise over the standard Log MMSE reference method. In babble noise, the estimator rendered similar SNR and SNRSeg values as the Log-MMSE reference method. Subjectively the residue background noise sounded more natural when using the suggested method. ©2009 IEEE.
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spelling curtin-20.500.11937-81052017-09-13T14:35:06Z Improved a priori SNR estimation with application in Log-MMSE speech estimation Höglund, N. Nordholm, Sven A speech enhancement method utilizing the harmonic structure of speech is presented. The method is an extension of the well known minimum mean square error log-spectral amplitude estimator(Log MMSE) method for speech enhancement. The improvement lies specifically on a priori SNR estimation by utilizing harmonic structure of speech. The method is based on a conditional averaging operation over adjacent frequency bands for each processed data block. The actual frequency bands used in the conditional averaging is determined by a pitch detector. Thus voiced segments are averaged over frequency according to the pitch and the corresponding harmonic structure of voiced speech. Non-voiced segments are averaged over frequency according to a random number depending on the pitch value. The result is overall better SNR and SNRSeg values in white noise over the standard Log MMSE reference method. In babble noise, the estimator rendered similar SNR and SNRSeg values as the Log-MMSE reference method. Subjectively the residue background noise sounded more natural when using the suggested method. ©2009 IEEE. 2009 Conference Paper http://hdl.handle.net/20.500.11937/8105 10.1109/ASPAA.2009.5346478 restricted
spellingShingle Höglund, N.
Nordholm, Sven
Improved a priori SNR estimation with application in Log-MMSE speech estimation
title Improved a priori SNR estimation with application in Log-MMSE speech estimation
title_full Improved a priori SNR estimation with application in Log-MMSE speech estimation
title_fullStr Improved a priori SNR estimation with application in Log-MMSE speech estimation
title_full_unstemmed Improved a priori SNR estimation with application in Log-MMSE speech estimation
title_short Improved a priori SNR estimation with application in Log-MMSE speech estimation
title_sort improved a priori snr estimation with application in log-mmse speech estimation
url http://hdl.handle.net/20.500.11937/8105