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Comparing Binaural Pre-processing Strategies I: Instrumental Evaluation

In a collaborative research project, several monaural and binaural noise reduction algorithms have been comprehensively evaluated. In this article, eight selected noise reduction algorithms were assessed using instrumental measures, with a focus on the instrumental evaluation of speech intelligibili...

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Autores principales: Baumgärtel, Regina M., Krawczyk-Becker, Martin, Marquardt, Daniel, Völker, Christoph, Hu, Hongmei, Herzke, Tobias, Coleman, Graham, Adiloğlu, Kamil, Ernst, Stephan M. A., Gerkmann, Timo, Doclo, Simon, Kollmeier, Birger, Hohmann, Volker, Dietz, Mathias
Formato: Online Artículo Texto
Lenguaje:English
Publicado: SAGE Publications 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4771044/
https://www.ncbi.nlm.nih.gov/pubmed/26721920
http://dx.doi.org/10.1177/2331216515617916
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author Baumgärtel, Regina M.
Krawczyk-Becker, Martin
Marquardt, Daniel
Völker, Christoph
Hu, Hongmei
Herzke, Tobias
Coleman, Graham
Adiloğlu, Kamil
Ernst, Stephan M. A.
Gerkmann, Timo
Doclo, Simon
Kollmeier, Birger
Hohmann, Volker
Dietz, Mathias
author_facet Baumgärtel, Regina M.
Krawczyk-Becker, Martin
Marquardt, Daniel
Völker, Christoph
Hu, Hongmei
Herzke, Tobias
Coleman, Graham
Adiloğlu, Kamil
Ernst, Stephan M. A.
Gerkmann, Timo
Doclo, Simon
Kollmeier, Birger
Hohmann, Volker
Dietz, Mathias
author_sort Baumgärtel, Regina M.
collection PubMed
description In a collaborative research project, several monaural and binaural noise reduction algorithms have been comprehensively evaluated. In this article, eight selected noise reduction algorithms were assessed using instrumental measures, with a focus on the instrumental evaluation of speech intelligibility. Four distinct, reverberant scenarios were created to reflect everyday listening situations: a stationary speech-shaped noise, a multitalker babble noise, a single interfering talker, and a realistic cafeteria noise. Three instrumental measures were employed to assess predicted speech intelligibility and predicted sound quality: the intelligibility-weighted signal-to-noise ratio, the short-time objective intelligibility measure, and the perceptual evaluation of speech quality. The results show substantial improvements in predicted speech intelligibility as well as sound quality for the proposed algorithms. The evaluated coherence-based noise reduction algorithm was able to provide improvements in predicted audio signal quality. For the tested single-channel noise reduction algorithm, improvements in intelligibility-weighted signal-to-noise ratio were observed in all but the nonstationary cafeteria ambient noise scenario. Binaural minimum variance distortionless response beamforming algorithms performed particularly well in all noise scenarios.
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spelling pubmed-47710442016-05-26 Comparing Binaural Pre-processing Strategies I: Instrumental Evaluation Baumgärtel, Regina M. Krawczyk-Becker, Martin Marquardt, Daniel Völker, Christoph Hu, Hongmei Herzke, Tobias Coleman, Graham Adiloğlu, Kamil Ernst, Stephan M. A. Gerkmann, Timo Doclo, Simon Kollmeier, Birger Hohmann, Volker Dietz, Mathias Trends Hear Special Issue In a collaborative research project, several monaural and binaural noise reduction algorithms have been comprehensively evaluated. In this article, eight selected noise reduction algorithms were assessed using instrumental measures, with a focus on the instrumental evaluation of speech intelligibility. Four distinct, reverberant scenarios were created to reflect everyday listening situations: a stationary speech-shaped noise, a multitalker babble noise, a single interfering talker, and a realistic cafeteria noise. Three instrumental measures were employed to assess predicted speech intelligibility and predicted sound quality: the intelligibility-weighted signal-to-noise ratio, the short-time objective intelligibility measure, and the perceptual evaluation of speech quality. The results show substantial improvements in predicted speech intelligibility as well as sound quality for the proposed algorithms. The evaluated coherence-based noise reduction algorithm was able to provide improvements in predicted audio signal quality. For the tested single-channel noise reduction algorithm, improvements in intelligibility-weighted signal-to-noise ratio were observed in all but the nonstationary cafeteria ambient noise scenario. Binaural minimum variance distortionless response beamforming algorithms performed particularly well in all noise scenarios. SAGE Publications 2015-12-16 /pmc/articles/PMC4771044/ /pubmed/26721920 http://dx.doi.org/10.1177/2331216515617916 Text en © The Author(s) 2015 http://creativecommons.org/licenses/by-nc/3.0/ This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 3.0 License (http://www.creativecommons.org/licenses/by-nc/3.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access page(https://us.sagepub.com/en-us/nam/open-access-at-sage).
spellingShingle Special Issue
Baumgärtel, Regina M.
Krawczyk-Becker, Martin
Marquardt, Daniel
Völker, Christoph
Hu, Hongmei
Herzke, Tobias
Coleman, Graham
Adiloğlu, Kamil
Ernst, Stephan M. A.
Gerkmann, Timo
Doclo, Simon
Kollmeier, Birger
Hohmann, Volker
Dietz, Mathias
Comparing Binaural Pre-processing Strategies I: Instrumental Evaluation
title Comparing Binaural Pre-processing Strategies I: Instrumental Evaluation
title_full Comparing Binaural Pre-processing Strategies I: Instrumental Evaluation
title_fullStr Comparing Binaural Pre-processing Strategies I: Instrumental Evaluation
title_full_unstemmed Comparing Binaural Pre-processing Strategies I: Instrumental Evaluation
title_short Comparing Binaural Pre-processing Strategies I: Instrumental Evaluation
title_sort comparing binaural pre-processing strategies i: instrumental evaluation
topic Special Issue
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4771044/
https://www.ncbi.nlm.nih.gov/pubmed/26721920
http://dx.doi.org/10.1177/2331216515617916
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