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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...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi Publishing Corporation
2014
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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. |
format | Online Article Text |
id | pubmed-4052886 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | Hindawi Publishing Corporation |
record_format | MEDLINE/PubMed |
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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