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Voice Activity Detection in Noisy Environments Based on Double-Combined Fourier Transform and Line Fitting

A new voice activity detector for noisy environments is proposed. In conventional algorithms, the endpoint of speech is found by applying an edge detection filter that finds the abrupt changing point in a feature domain. However, since the frame energy feature is unstable in noisy environments, it i...

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Detalles Bibliográficos
Autores principales: Park, Jinsoo, Kim, Wooil, Han, David K., Ko, Hanseok
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi Publishing Corporation 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4142156/
https://www.ncbi.nlm.nih.gov/pubmed/25170520
http://dx.doi.org/10.1155/2014/146040
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author Park, Jinsoo
Kim, Wooil
Han, David K.
Ko, Hanseok
author_facet Park, Jinsoo
Kim, Wooil
Han, David K.
Ko, Hanseok
author_sort Park, Jinsoo
collection PubMed
description A new voice activity detector for noisy environments is proposed. In conventional algorithms, the endpoint of speech is found by applying an edge detection filter that finds the abrupt changing point in a feature domain. However, since the frame energy feature is unstable in noisy environments, it is difficult to accurately find the endpoint of speech. Therefore, a novel feature extraction algorithm based on the double-combined Fourier transform and envelope line fitting is proposed. It is combined with an edge detection filter for effective detection of endpoints. Effectiveness of the proposed algorithm is evaluated and compared to other VAD algorithms using two different databases, which are AURORA 2.0 database and SITEC database. Experimental results show that the proposed algorithm performs well under a variety of noisy conditions.
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spelling pubmed-41421562014-08-28 Voice Activity Detection in Noisy Environments Based on Double-Combined Fourier Transform and Line Fitting Park, Jinsoo Kim, Wooil Han, David K. Ko, Hanseok ScientificWorldJournal Research Article A new voice activity detector for noisy environments is proposed. In conventional algorithms, the endpoint of speech is found by applying an edge detection filter that finds the abrupt changing point in a feature domain. However, since the frame energy feature is unstable in noisy environments, it is difficult to accurately find the endpoint of speech. Therefore, a novel feature extraction algorithm based on the double-combined Fourier transform and envelope line fitting is proposed. It is combined with an edge detection filter for effective detection of endpoints. Effectiveness of the proposed algorithm is evaluated and compared to other VAD algorithms using two different databases, which are AURORA 2.0 database and SITEC database. Experimental results show that the proposed algorithm performs well under a variety of noisy conditions. Hindawi Publishing Corporation 2014 2014-08-06 /pmc/articles/PMC4142156/ /pubmed/25170520 http://dx.doi.org/10.1155/2014/146040 Text en Copyright © 2014 Jinsoo Park 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
Park, Jinsoo
Kim, Wooil
Han, David K.
Ko, Hanseok
Voice Activity Detection in Noisy Environments Based on Double-Combined Fourier Transform and Line Fitting
title Voice Activity Detection in Noisy Environments Based on Double-Combined Fourier Transform and Line Fitting
title_full Voice Activity Detection in Noisy Environments Based on Double-Combined Fourier Transform and Line Fitting
title_fullStr Voice Activity Detection in Noisy Environments Based on Double-Combined Fourier Transform and Line Fitting
title_full_unstemmed Voice Activity Detection in Noisy Environments Based on Double-Combined Fourier Transform and Line Fitting
title_short Voice Activity Detection in Noisy Environments Based on Double-Combined Fourier Transform and Line Fitting
title_sort voice activity detection in noisy environments based on double-combined fourier transform and line fitting
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4142156/
https://www.ncbi.nlm.nih.gov/pubmed/25170520
http://dx.doi.org/10.1155/2014/146040
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