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Time-domain features and probabilistic neural network for the detection of vocal fold pathology

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Main Authors: Hariharan, Muthusamy, Paulraj, Murugesa Pandiyan, Prof. Madya, Sazali, Yaacob, Prof. Dr.
Other Authors: wavelet.hari@gmail.com
Format: Article
Language:English
Published: Universiti Malaya 2010
Subjects:
Acoustic analysis
Vocal fold pathology
Time-domain features
Probabilistic neural network
Online Access:http://dspace.unimap.edu.my/xmlui/handle/123456789/10222
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spelling my.unimap-102222010-11-16T01:04:48Z Time-domain features and probabilistic neural network for the detection of vocal fold pathology Hariharan, Muthusamy Paulraj, Murugesa Pandiyan, Prof. Madya Sazali, Yaacob, Prof. Dr. wavelet.hari@gmail.com paul@unimap.edu.my s.yaacob@unimap.edu.my Acoustic analysis Vocal fold pathology Time-domain features Probabilistic neural network Link to publisher's homepage at http://www.um.edu.my/ Due to the nature of job, unhealthy social habits and voice abuse, people are subjected to the risk of voice problems. It is well known that most of vocal fold pathologies cause changes in the acoustic voice signal. Therefore, the voice signal can be a useful tool to diagnose them. Acoustic voice analysis can be used to characterize the pathological voices. This paper presents the detection of vocal fold pathology with the aid of the speech signal recorded from the patients. The speech samples from Massachusetts Eye and Ear Infirmary (MEEI) database are used to evaluate the scheme. Time-domain features based on energy variation are proposed and extracted from the speech to form a feature vector. In order to test the effectiveness and reliability of the proposed time-domain features, a Probabilistic Neural Network (PNN) is employed. The experimental results show that the proposed features gives very promising classification accuracy and can be effectively used to detect the vocal fold pathology clinically. 2010-11-16T01:04:48Z 2010-11-16T01:04:48Z 2010 Article Malaysian Journal of Computer Science, vol. 23(1), 2010, pages 60-67 0127-9084 http://mjcs.fsktm.um.edu.my/document.aspx?FileName=878.pdf http://hdl.handle.net/123456789/10222 en Universiti Malaya
institution Universiti Malaysia Perlis
building UniMAP Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Perlis
content_source UniMAP Library Digital Repository
url_provider http://dspace.unimap.edu.my/
language English
topic Acoustic analysis
Vocal fold pathology
Time-domain features
Probabilistic neural network
spellingShingle Acoustic analysis
Vocal fold pathology
Time-domain features
Probabilistic neural network
Hariharan, Muthusamy
Paulraj, Murugesa Pandiyan, Prof. Madya
Sazali, Yaacob, Prof. Dr.
Time-domain features and probabilistic neural network for the detection of vocal fold pathology
description Link to publisher's homepage at http://www.um.edu.my/
author2 wavelet.hari@gmail.com
author_facet wavelet.hari@gmail.com
Hariharan, Muthusamy
Paulraj, Murugesa Pandiyan, Prof. Madya
Sazali, Yaacob, Prof. Dr.
format Article
author Hariharan, Muthusamy
Paulraj, Murugesa Pandiyan, Prof. Madya
Sazali, Yaacob, Prof. Dr.
author_sort Hariharan, Muthusamy
title Time-domain features and probabilistic neural network for the detection of vocal fold pathology
title_short Time-domain features and probabilistic neural network for the detection of vocal fold pathology
title_full Time-domain features and probabilistic neural network for the detection of vocal fold pathology
title_fullStr Time-domain features and probabilistic neural network for the detection of vocal fold pathology
title_full_unstemmed Time-domain features and probabilistic neural network for the detection of vocal fold pathology
title_sort time-domain features and probabilistic neural network for the detection of vocal fold pathology
publisher Universiti Malaya
publishDate 2010
url http://dspace.unimap.edu.my/xmlui/handle/123456789/10222
_version_ 1643789790016962560
score 13.214268

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