Assessment of hypernasality for children with cleft palate based on cepstrum analysis

Hypernasality is a frequently occurring resonance disorder in children with cleft palate. In general, an operation is necessary to reduce the hypernasality and therefore an assessment of hypernasality is imperative to quantify the effect of the surgery and design the speech therapy sessions, which a...

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Main Authors: Ehsan Akafi, Mansour Vali, Negin Moradi, Kowsar Baghban
Format: Article
Language:English
Published: Wolters Kluwer Medknow Publications 2013-01-01
Series:Journal of Medical Signals and Sensors
Subjects:
Online Access:http://www.jmss.mui.ac.ir/article.asp?issn=2228-7477;year=2013;volume=3;issue=4;spage=209;epage=215;aulast=Akafi
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spelling doaj-6e60cdd3be9c473388d89b16022e25ef2020-11-25T00:12:03ZengWolters Kluwer Medknow PublicationsJournal of Medical Signals and Sensors2228-74772013-01-0134209215Assessment of hypernasality for children with cleft palate based on cepstrum analysisEhsan AkafiMansour ValiNegin MoradiKowsar BaghbanHypernasality is a frequently occurring resonance disorder in children with cleft palate. In general, an operation is necessary to reduce the hypernasality and therefore an assessment of hypernasality is imperative to quantify the effect of the surgery and design the speech therapy sessions, which are crucial after surgery. In this paper, a new quantitative method is proposed to estimate hypernasality. The proposed method used the fact that an autoregressive (AR) model for vocal tract system of a patient with hypernasal speech is not accurate; because of the zeros appear in the frequency response of the vocal tract system. Therefore in our method, hypernasality was estimated by a quantity calculated from comparing the distance between the sequences of cepstrum coefficients extracted from AR model and autoregressive moving average model. K-means and Bayes theorem were utilized to classify the utterances of subjects by means of proposed index. We achieved the accuracy up to 81.12% on utterances and 97.14% on subjects. Since the proposed method needs only computer processing of speech data, compared with other clinical methods it provides a simple evaluation of hypernasality.http://www.jmss.mui.ac.ir/article.asp?issn=2228-7477;year=2013;volume=3;issue=4;spage=209;epage=215;aulast=AkafiCepstrumcleft palatehypernasalityspeech processingspeech therapy
collection DOAJ
language English
format Article
sources DOAJ
author Ehsan Akafi
Mansour Vali
Negin Moradi
Kowsar Baghban
spellingShingle Ehsan Akafi
Mansour Vali
Negin Moradi
Kowsar Baghban
Assessment of hypernasality for children with cleft palate based on cepstrum analysis
Journal of Medical Signals and Sensors
Cepstrum
cleft palate
hypernasality
speech processing
speech therapy
author_facet Ehsan Akafi
Mansour Vali
Negin Moradi
Kowsar Baghban
author_sort Ehsan Akafi
title Assessment of hypernasality for children with cleft palate based on cepstrum analysis
title_short Assessment of hypernasality for children with cleft palate based on cepstrum analysis
title_full Assessment of hypernasality for children with cleft palate based on cepstrum analysis
title_fullStr Assessment of hypernasality for children with cleft palate based on cepstrum analysis
title_full_unstemmed Assessment of hypernasality for children with cleft palate based on cepstrum analysis
title_sort assessment of hypernasality for children with cleft palate based on cepstrum analysis
publisher Wolters Kluwer Medknow Publications
series Journal of Medical Signals and Sensors
issn 2228-7477
publishDate 2013-01-01
description Hypernasality is a frequently occurring resonance disorder in children with cleft palate. In general, an operation is necessary to reduce the hypernasality and therefore an assessment of hypernasality is imperative to quantify the effect of the surgery and design the speech therapy sessions, which are crucial after surgery. In this paper, a new quantitative method is proposed to estimate hypernasality. The proposed method used the fact that an autoregressive (AR) model for vocal tract system of a patient with hypernasal speech is not accurate; because of the zeros appear in the frequency response of the vocal tract system. Therefore in our method, hypernasality was estimated by a quantity calculated from comparing the distance between the sequences of cepstrum coefficients extracted from AR model and autoregressive moving average model. K-means and Bayes theorem were utilized to classify the utterances of subjects by means of proposed index. We achieved the accuracy up to 81.12% on utterances and 97.14% on subjects. Since the proposed method needs only computer processing of speech data, compared with other clinical methods it provides a simple evaluation of hypernasality.
topic Cepstrum
cleft palate
hypernasality
speech processing
speech therapy
url http://www.jmss.mui.ac.ir/article.asp?issn=2228-7477;year=2013;volume=3;issue=4;spage=209;epage=215;aulast=Akafi
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AT neginmoradi assessmentofhypernasalityforchildrenwithcleftpalatebasedoncepstrumanalysis
AT kowsarbaghban assessmentofhypernasalityforchildrenwithcleftpalatebasedoncepstrumanalysis
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