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Automatic speech recognition for dysphonic patients by using oriented local features

The number of patients with voice pathology has increased significantly in recent years. The disability or illness of a person should not deprive him from taking benefits of the technology advances that is changing the daily life. For example, modern day speech recognition technology should be capab...

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Main Authors: Ali, Z., Muhammad, G., Alsulaiman, M., Elamvazuthi, I., Al-Mutib, K.
Format: Conference or Workshop Item
Published: International Society of Computers and Their Applications (ISCA) 2014
Online Access:https://www.scopus.com/inward/record.uri?eid=2-s2.0-84913598714&partnerID=40&md5=4d138ace7c38a0c467ceb5bbbf8fa9a8
http://eprints.utp.edu.my/32008/
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spelling my.utp.eprints.320082022-03-29T04:05:09Z Automatic speech recognition for dysphonic patients by using oriented local features Ali, Z. Muhammad, G. Alsulaiman, M. Elamvazuthi, I. Al-Mutib, K. The number of patients with voice pathology has increased significantly in recent years. The disability or illness of a person should not deprive him from taking benefits of the technology advances that is changing the daily life. For example, modern day speech recognition technology should be capable to recognize a speech from a normal person as well as a person having dysphonic. In this paper, we propose a new speech feature to use in automatic speech recognition system of disordered speech. We compare the performance of this feature with the most widely used speech feature in speech recognition. The comparison is done using spoken words uttered by both normal and dysphonic patients. The obtained results with the proposed technique are good and comparable to the existing method. Copyright ISCA, CAINE 2014. International Society of Computers and Their Applications (ISCA) 2014 Conference or Workshop Item NonPeerReviewed https://www.scopus.com/inward/record.uri?eid=2-s2.0-84913598714&partnerID=40&md5=4d138ace7c38a0c467ceb5bbbf8fa9a8 Ali, Z. and Muhammad, G. and Alsulaiman, M. and Elamvazuthi, I. and Al-Mutib, K. (2014) Automatic speech recognition for dysphonic patients by using oriented local features. In: UNSPECIFIED. http://eprints.utp.edu.my/32008/
institution Universiti Teknologi Petronas
building UTP Resource Centre
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Petronas
content_source UTP Institutional Repository
url_provider http://eprints.utp.edu.my/
description The number of patients with voice pathology has increased significantly in recent years. The disability or illness of a person should not deprive him from taking benefits of the technology advances that is changing the daily life. For example, modern day speech recognition technology should be capable to recognize a speech from a normal person as well as a person having dysphonic. In this paper, we propose a new speech feature to use in automatic speech recognition system of disordered speech. We compare the performance of this feature with the most widely used speech feature in speech recognition. The comparison is done using spoken words uttered by both normal and dysphonic patients. The obtained results with the proposed technique are good and comparable to the existing method. Copyright ISCA, CAINE 2014.
format Conference or Workshop Item
author Ali, Z.
Muhammad, G.
Alsulaiman, M.
Elamvazuthi, I.
Al-Mutib, K.
spellingShingle Ali, Z.
Muhammad, G.
Alsulaiman, M.
Elamvazuthi, I.
Al-Mutib, K.
Automatic speech recognition for dysphonic patients by using oriented local features
author_facet Ali, Z.
Muhammad, G.
Alsulaiman, M.
Elamvazuthi, I.
Al-Mutib, K.
author_sort Ali, Z.
title Automatic speech recognition for dysphonic patients by using oriented local features
title_short Automatic speech recognition for dysphonic patients by using oriented local features
title_full Automatic speech recognition for dysphonic patients by using oriented local features
title_fullStr Automatic speech recognition for dysphonic patients by using oriented local features
title_full_unstemmed Automatic speech recognition for dysphonic patients by using oriented local features
title_sort automatic speech recognition for dysphonic patients by using oriented local features
publisher International Society of Computers and Their Applications (ISCA)
publishDate 2014
url https://www.scopus.com/inward/record.uri?eid=2-s2.0-84913598714&partnerID=40&md5=4d138ace7c38a0c467ceb5bbbf8fa9a8
http://eprints.utp.edu.my/32008/
_version_ 1738657327307816960
score 13.211869

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