An investigation of MDVP parameters for voice pathology detection on three different databases

In this paper, an investigation of Multi-Dimensional Voice Program (MDVP) parameters to automatically detect voice pathology in three different databases was conducted. MDVP parameters are very popular acoustic analysis among physician / clinician to detect voice pathology. The main objective of the paper is to find out the most prominent MDVP parameters irrespective to the databases used. In this study, three different databases from three distinct languages were used. The databases are Arabic voice pathology database (AVPD), Massachusetts Eye and Ear Infirmary (MEEI) (English database), and Saarbruecken Voice Database (SVD) (German database). Only the sustained vowel /a/ was used in the study. Fisher discrimination ratio (FDR) was applied to rank the parameters. Support vector machine (SVM) was used to perform the detection process. The experimental results demonstrated that there was clear difference of the performance of the MDVP parameters using these databases. The highly ranked parameters were also different from one database to another. The accuracies that achieved are varied from one database to another with the same number of MVPD parameters. The best accuracies obtained by using the three highest MDVP parameters arranged according to FDR were 99.68%, 88.21% and 72.53 for SVD, MEEI and AVPD, respectively.