{"title":"Voice Pathology Detection Using Vocal Tract Area","authors":"Muhammad Ghulam","doi":"10.1109/EMS.2013.29","DOIUrl":null,"url":null,"abstract":"In this paper, we develop an automatic voice pathology detection (VPD) system based on voice production theory. More specifically, we extract features from vocal tract area function from the tubes, which are closely located to the glottis. Voice pathology is related to a vocal fold problem, and hence the vocal tract area connected to the vocal fold or the glottis should exhibit irregular patterns over frames in case of a sustained vowel for a pathological voice. This irregular pattern is quantified in the form of variance across the frames to distinguish between normal and pathological voices. The proposed VPD system is evaluated on the MEEI database with sustained vowel samples and achieves 99.02%±0.01 accuracy.","PeriodicalId":350614,"journal":{"name":"European Symposium on Computer Modeling and Simulation","volume":"15 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"European Symposium on Computer Modeling and Simulation","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/EMS.2013.29","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5
Abstract
In this paper, we develop an automatic voice pathology detection (VPD) system based on voice production theory. More specifically, we extract features from vocal tract area function from the tubes, which are closely located to the glottis. Voice pathology is related to a vocal fold problem, and hence the vocal tract area connected to the vocal fold or the glottis should exhibit irregular patterns over frames in case of a sustained vowel for a pathological voice. This irregular pattern is quantified in the form of variance across the frames to distinguish between normal and pathological voices. The proposed VPD system is evaluated on the MEEI database with sustained vowel samples and achieves 99.02%±0.01 accuracy.