Detection of Vocal Cyst Problem by Using High Order Moments and Support Vector Machines

Derya YILMAZ; Haydar ANKIŞHAN

doi:https://doi.org/10.21541/apjes.380271

Makale detayları

Detection of Vocal Cyst Problem by Using High Order Moments and Support Vector Machines

Yazarlar:

Derya YILMAZ | Haydar ANKIŞHAN

Yayıncı:

Akademik Perspektif Derneği

Ana Başlıklar:

Uygulamalı fizik

Dergi:

Academic Platform - Journal of Engineering and Science 2018 Vol.6 Issue 3, pp.97-103

Belge Tipi:

Makale

Yayın Tarihi:

9/2018

Belge Dili:

İngilizce

Document ID (Org No.):

2000874875

Sıklık:

Aylık

eISSN:

2822-2385

DOI:

https://doi.org/10.21541/apjes.380271

Anahtar kelimeler:

Özet:

 


The voice disorders occurring due to the problems in the
voice producing organs cause some changes in the intensity or tone of the
voice. It is difficult to identify the diseased voice by the reason of its
variable and different nature. One of the most popular voice disorder reasons is cyst
which is located on the vocal cords. The aim of this study is to detect the
vocal cyst problem by using acoustic voices data which were recorded from
healthy people and patient with cyst diagnoses
subjects by using high order statistics and support vector machines
(SVMs) classifier. In this study, two
experimental procedures were implemented for two different voice samples. In
the first, /a/ vowel and the second, the Turkish word of “aydınlık” (mean in
English “bright”) were investigated with skewness and kurtosis parameters which
are third and fourth order cumulants (spectral moments), respectively. The
obtained features values for healthy and cyst subjects were used as the SVMs’ inputs for classification. The experimental results show that the test
accuracies of SVMs were found as 94.89%
and 91.11% for /a/ vowel and “aydınlık” word, respectively. It is concluded from experimental studies that skewness provides more meaningful results than
kurtosis in relation to distinguish into two
voice groups as healthy and cyst.
Additionally, it is assessed that the “aydınlık” is affective word for the pathological and normal acoustic voice
discrimination as good as /a/vowel.

.

 


The voice disorders occurring due to the problems in the voice producing organs cause some changes in the intensity or tone of the voice. It is difficult to identify the diseased voice by the reason of its variable and different nature. One of the most popular voice disorder reasons is cyst which is located on the vocal cords. The aim of this study is to detect the vocal cyst problem by using acoustic voices data which were recorded from healthy people and patient with cyst diagnoses subjects by using high order statistics and support vector machines (SVMs) classifier. In this study, two experimental procedures were implemented for two different voice samples. In the first, /a/ vowel and the second, the Turkish word of “aydınlık” (mean in English “bright”) were investigated with skewness and kurtosis parameters which are third and fourth order cumulants (spectral moments), respectively. The obtained features values for healthy and cyst subjects were used as the SVMs’ inputs for classification. The experimental results show that the test accuracies of SVMs were found as 94.89% and 91.11% for /a/ vowel and “aydınlık” word, respectively. It is concluded from experimental studies that skewness provides more meaningful results than kurtosis in relation to distinguish into two voice groups as healthy and cyst. Additionally, it is assessed that the “aydınlık” is affective word for the pathological and normal acoustic voice discrimination as good as /a/vowel.


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Makale detayları

Detection of Vocal Cyst Problem by Using High Order Moments and Support Vector Machines

Yazarlar:

Derya YILMAZ | Haydar ANKIŞHAN

Yayıncı:

Akademik Perspektif Derneği

Ana Başlıklar:

Uygulamalı fizik

Dergi:

Academic Platform - Journal of Engineering and Science 2018 Vol.6 Issue 3, pp.97-103

Belge Tipi:

Makale

Yayın Tarihi:

9/2018

Belge Dili:

İngilizce

Document ID (Org No.):

2000874875

Sıklık:

Aylık

eISSN:

2822-2385

DOI:

https://doi.org/10.21541/apjes.380271

ses bozuklukları

vokal kist

çarpıklık

basıklık

destek vektör makineler

Sayı

Makale detayları

Detection of Vocal Cyst Problem by Using High Order Moments and Support Vector Machines

Yazarlar: Derya YILMAZ | Haydar ANKIŞHAN

Yayıncı: Akademik Perspektif Derneği

Ana Başlıklar: Uygulamalı fizik

Dergi: Academic Platform - Journal of Engineering and Science 2018 Vol.6 Issue 3, pp.97-103

Belge Tipi: Makale

Yayın Tarihi: 9/2018

Belge Dili: İngilizce

Document ID (Org No.): 2000874875

Sıklık: Aylık

eISSN: 2822-2385

DOI: https://doi.org/10.21541/apjes.380271

ses bozuklukları

vokal kist

çarpıklık

basıklık

destek vektör makineler

Sayı

Yazarlar:

Derya YILMAZ | Haydar ANKIŞHAN

Yayıncı:

Akademik Perspektif Derneği

Ana Başlıklar:

Uygulamalı fizik

Dergi:

Academic Platform - Journal of Engineering and Science 2018 Vol.6 Issue 3, pp.97-103

Belge Tipi:

Makale

Yayın Tarihi:

9/2018

Belge Dili:

İngilizce

Document ID (Org No.):

2000874875

Sıklık:

Aylık

eISSN:

2822-2385

DOI:

https://doi.org/10.21541/apjes.380271