TY  - CONF
Y1  - 2015///
SN  - 9781479976263
PB  - Institute of Electrical and Electronics Engineers Inc.
UR  - https://www.scopus.com/inward/record.uri?eid=2-s2.0-84964033974&doi=10.1109%2fNSITNSW.2015.7176431&partnerID=40&md5=1148ce43257f3b39f17c6439227a60aa
A1  - Al-Nasheri, A.
A1  - Ali, Z.
A1  - Muhammad, G.
A1  - Alsulaiman, M.
A1  - Almalki, K.H.
A1  - Mesallam, T.A.
A1  - Farahat, M.
AV  - none
N1  - cited By 8; Conference of 5th National Symposium on Information Technology: Towards New Smart World, NSITNSW 2015 ; Conference Date: 17 February 2015 Through 19 February 2015; Conference Code:117055
N2  - This paper investigates the use of MultiDimensional 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. © 2015 IEEE.
KW  - Classification (of information); Database systems; Pathology
KW  -  Acoustic features; Automatic speech recognition; AVPD; Commercial software; MDVP; MEEI; Pathological voice; Voice pathology detection
KW  -  Speech recognition
ID  - scholars5805
TI  - Voice pathology detection with MDVP parameters using Arabic voice pathology database
ER  -