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Comparison of speech parameterization techniques for the classification of speech disfluencies

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Main Authors: Chong, Yen Fook, Hariharan, Muthusamy, Dr., Lim, Sin Chee, Sazali, Yaacob, Prof. Dr., Abdul Hamid, Adom, Prof. Dr.
Other Authors: fook1987@gmail.com
Format: Article
Language:English
Published: Scientific and Technical Research Council of Turkey 2014
Subjects:
Disfluent speech
Linear predictive coding
Mel-frequency cepstral coefficient
Perceptual linear predictive analysis
Support vector machine
Online Access:http://dspace.unimap.edu.my:80/dspace/handle/123456789/33096
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spelling my.unimap-330962014-03-25T01:40:30Z Comparison of speech parameterization techniques for the classification of speech disfluencies Chong, Yen Fook Hariharan, Muthusamy, Dr. Lim, Sin Chee Sazali, Yaacob, Prof. Dr. Abdul Hamid, Adom, Prof. Dr. fook1987@gmail.com hari@unimap.edu.my sclim3@gmail.com s.yaacob@unimap.edu.my abdhamid@unimap.edu.my Disfluent speech Linear predictive coding Mel-frequency cepstral coefficient Perceptual linear predictive analysis Support vector machine Link to publisher's homepage at http://www.tubitak.gov.tr/ Stuttering assessment through the manual classification of speech disfluencies is subjective, inconsistent, time-consuming, and prone to error. The aim of this paper is to compare the effectiveness of the 3 speech feature extraction methods, mel-frequency cepstral coefficients, linear predictive coding (LPC)-based cepstral parameters, and perceptual linear predictive (PLP) analysis, for classifying 2 types of speech disfluencies, repetition and prolongation, from recorded disfluent speech samples. Three different classifiers, the k-nearest neighbor classifier, linear discriminant analysis-based classifier, and support vector machine, are employed for the classification of speech disfluencies. Speech samples are taken from the University College London Archive of Stuttered Speech and stuttered events are identified through manual segmentation. A 10-fold cross-validation method is used for testing the reliability of the classifier results. The effect of the 2 parameters (LPC order and frame length) in the LPC- and PLP-based methods on the classification results is also investigated. The experimental results reveal that the proposed method can be used to help speech language pathologists in classifying speech disfluencies. 2014-03-25T01:40:30Z 2014-03-25T01:40:30Z 2013-12 Article Turkish Journal of Electrical Engineering and Computer Sciences, vol. 21(SUPPL. 1), 2013, pages 1983-1994 1300-0632 http://mistug.tubitak.gov.tr/bdyim/toc.php?dergi=elk&yilsayi=2013/Sup.1 http://dspace.unimap.edu.my:80/dspace/handle/123456789/33096 en Scientific and Technical Research Council of Turkey
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 Disfluent speech
Linear predictive coding
Mel-frequency cepstral coefficient
Perceptual linear predictive analysis
Support vector machine
spellingShingle Disfluent speech
Linear predictive coding
Mel-frequency cepstral coefficient
Perceptual linear predictive analysis
Support vector machine
Chong, Yen Fook
Hariharan, Muthusamy, Dr.
Lim, Sin Chee
Sazali, Yaacob, Prof. Dr.
Abdul Hamid, Adom, Prof. Dr.
Comparison of speech parameterization techniques for the classification of speech disfluencies
description Link to publisher's homepage at http://www.tubitak.gov.tr/
author2 fook1987@gmail.com
author_facet fook1987@gmail.com
Chong, Yen Fook
Hariharan, Muthusamy, Dr.
Lim, Sin Chee
Sazali, Yaacob, Prof. Dr.
Abdul Hamid, Adom, Prof. Dr.
format Article
author Chong, Yen Fook
Hariharan, Muthusamy, Dr.
Lim, Sin Chee
Sazali, Yaacob, Prof. Dr.
Abdul Hamid, Adom, Prof. Dr.
author_sort Chong, Yen Fook
title Comparison of speech parameterization techniques for the classification of speech disfluencies
title_short Comparison of speech parameterization techniques for the classification of speech disfluencies
title_full Comparison of speech parameterization techniques for the classification of speech disfluencies
title_fullStr Comparison of speech parameterization techniques for the classification of speech disfluencies
title_full_unstemmed Comparison of speech parameterization techniques for the classification of speech disfluencies
title_sort comparison of speech parameterization techniques for the classification of speech disfluencies
publisher Scientific and Technical Research Council of Turkey
publishDate 2014
url http://dspace.unimap.edu.my:80/dspace/handle/123456789/33096
_version_ 1643797066324901888
score 13.214268

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