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A Hierarchical Framework Approach for Voice Activity Detection and Speech Enhancement

Accurate and effective voice activity detection (VAD) is a fundamental step for robust speech or speaker recognition. In this study, we proposed a hierarchical framework approach for VAD and speech enhancement. The modified Wiener filter (MWF) approach is utilized for noise reduction in the speech e...

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Detalles Bibliográficos
Autores principales: Zhang, Yan, Tang, Zhen-min, Li, Yan-ping, Luo, Yang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi Publishing Corporation 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4052886/
https://www.ncbi.nlm.nih.gov/pubmed/24959621
http://dx.doi.org/10.1155/2014/723643
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author Zhang, Yan
Tang, Zhen-min
Li, Yan-ping
Luo, Yang
author_facet Zhang, Yan
Tang, Zhen-min
Li, Yan-ping
Luo, Yang
author_sort Zhang, Yan
collection PubMed
description Accurate and effective voice activity detection (VAD) is a fundamental step for robust speech or speaker recognition. In this study, we proposed a hierarchical framework approach for VAD and speech enhancement. The modified Wiener filter (MWF) approach is utilized for noise reduction in the speech enhancement block. For the feature selection and voting block, several discriminating features were employed in a voting paradigm for the consideration of reliability and discriminative power. Effectiveness of the proposed approach is compared and evaluated to other VAD techniques by using two well-known databases, namely, TIMIT database and NOISEX-92 database. Experimental results show that the proposed method performs well under a variety of noisy conditions.
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spelling pubmed-40528862014-06-23 A Hierarchical Framework Approach for Voice Activity Detection and Speech Enhancement Zhang, Yan Tang, Zhen-min Li, Yan-ping Luo, Yang ScientificWorldJournal Research Article Accurate and effective voice activity detection (VAD) is a fundamental step for robust speech or speaker recognition. In this study, we proposed a hierarchical framework approach for VAD and speech enhancement. The modified Wiener filter (MWF) approach is utilized for noise reduction in the speech enhancement block. For the feature selection and voting block, several discriminating features were employed in a voting paradigm for the consideration of reliability and discriminative power. Effectiveness of the proposed approach is compared and evaluated to other VAD techniques by using two well-known databases, namely, TIMIT database and NOISEX-92 database. Experimental results show that the proposed method performs well under a variety of noisy conditions. Hindawi Publishing Corporation 2014 2014-05-12 /pmc/articles/PMC4052886/ /pubmed/24959621 http://dx.doi.org/10.1155/2014/723643 Text en Copyright © 2014 Yan Zhang et al. https://creativecommons.org/licenses/by/3.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Zhang, Yan
Tang, Zhen-min
Li, Yan-ping
Luo, Yang
A Hierarchical Framework Approach for Voice Activity Detection and Speech Enhancement
title A Hierarchical Framework Approach for Voice Activity Detection and Speech Enhancement
title_full A Hierarchical Framework Approach for Voice Activity Detection and Speech Enhancement
title_fullStr A Hierarchical Framework Approach for Voice Activity Detection and Speech Enhancement
title_full_unstemmed A Hierarchical Framework Approach for Voice Activity Detection and Speech Enhancement
title_short A Hierarchical Framework Approach for Voice Activity Detection and Speech Enhancement
title_sort hierarchical framework approach for voice activity detection and speech enhancement
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4052886/
https://www.ncbi.nlm.nih.gov/pubmed/24959621
http://dx.doi.org/10.1155/2014/723643
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