{"title":"LPC modelling and cepstral analysis applied to vocal fold pathology detection","authors":"B. Neto, S. C. Costa, J. Fechine","doi":"10.1504/IJFIPM.2008.020185","DOIUrl":null,"url":null,"abstract":"Laryngeal pathologies are generally diagnosed using laryngoscopical exams, which are considered invasive to patients. Digital signal processing techniques are noninvasive and can be applied to perform an acoustic analysis for vocal quality assessment providing an objective diagnosis of pathological voices. This paper aims at specifying and evaluating the acoustic features for vocal fold edema through a parametric modelling based on the resonant structure of the human speech production mechanism by LPC and LPC-based cepstral coefficients and a nonparametric approach related to human auditory perception system by mel-frequency cepstral coefficients. A vector-quantising-trained distance classifier is used in the discrimination process.","PeriodicalId":216126,"journal":{"name":"Int. J. Funct. Informatics Pers. Medicine","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Int. J. Funct. Informatics Pers. Medicine","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1504/IJFIPM.2008.020185","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
Abstract
Laryngeal pathologies are generally diagnosed using laryngoscopical exams, which are considered invasive to patients. Digital signal processing techniques are noninvasive and can be applied to perform an acoustic analysis for vocal quality assessment providing an objective diagnosis of pathological voices. This paper aims at specifying and evaluating the acoustic features for vocal fold edema through a parametric modelling based on the resonant structure of the human speech production mechanism by LPC and LPC-based cepstral coefficients and a nonparametric approach related to human auditory perception system by mel-frequency cepstral coefficients. A vector-quantising-trained distance classifier is used in the discrimination process.