Voice pathology detection with MDVP parameters using Arabic voice pathology database

Author

Al-nasheri, Ahmed ; Ali, Zulfiqar ; Muhammad, Ghulam ; Alsulaiman, Mansour ; Almalki, Khalid H. ; Mesallam, Tamer A. ; Farahat, Mohamed

Author_Institution

Dept. of Comput. Eng., King Saud Univ., Riyadh, Saudi Arabia

fYear

2015

fDate

17-19 Feb. 2015

Firstpage

1

Lastpage

5

Abstract

This paper investigates the use of Multi-Dimensional Voice Program (MDVP) parameters to automatically detect voice pathology in Arabic voice pathology database (AVPD). MDVP parameters are very popular among the physician / clinician to detect voice pathology; however, MDVP is a commercial software. AVPD is a newly developed speech database designed to suit a wide range of experiments in the field of automatic voice pathology detection, classification, and automatic speech recognition. This paper is the first step to evaluate MDVP parameters in AVPD using sustained vowel /a/. The experimental results demonstrate that some of the acoustic features show an excellent ability to discriminate between normal and pathological voices. The overall best accuracy is 81.33% by using SVM classifier.

Keywords

medical signal detection; signal classification; speech recognition; support vector machines; AVPD; Arabic voice pathology database; MDVP parameters; SVM classifier; acoustic features; automatic speech recognition; commercial software; multidimensional voice program; speech database; support vector machine; voice pathology detection; Accuracy; Acoustics; Databases; Pathology; Speech; Speech recognition; Support vector machines; AVPD; MDVP; MEEI; SVM; voice pathology detection;

fLanguage

English

Publisher

ieee

Conference_Titel

Information Technology: Towards New Smart World (NSITNSW), 2015 5th National Symposium on

Conference_Location

Riyadh

Print_ISBN

978-1-4799-7625-6

Type

conf

DOI

10.1109/NSITNSW.2015.7176431

Filename

7176431