P. Gómez, Francisco Díaz Pérez, Agustín Álvarez Marquina, Katherine Murphy, C. Lázaro, R. Martínez, M. V. R. Biarge
{"title":"Principal component analysis of spectral perturbation parameters for voice pathology detection","authors":"P. Gómez, Francisco Díaz Pérez, Agustín Álvarez Marquina, Katherine Murphy, C. Lázaro, R. Martínez, M. V. R. Biarge","doi":"10.1109/CBMS.2005.88","DOIUrl":null,"url":null,"abstract":"In recent years emphasis has been placed upon the early detection of voice pathologies by using the signal processing of voice to evaluate certain time and spectrum domain parameters which may infer the presence of pathology. The present work is aimed at establishing the suitability of these voice spectral parameters in fixing a clear distinction between pathologic and normophonic voice, and to further classify the specific patient's pathology. Principal component analysis is used in parameter selection. Results for normal and pathological samples will be presented and discussed.","PeriodicalId":119367,"journal":{"name":"18th IEEE Symposium on Computer-Based Medical Systems (CBMS'05)","volume":"69 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2005-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"14","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"18th IEEE Symposium on Computer-Based Medical Systems (CBMS'05)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CBMS.2005.88","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 14
Abstract
In recent years emphasis has been placed upon the early detection of voice pathologies by using the signal processing of voice to evaluate certain time and spectrum domain parameters which may infer the presence of pathology. The present work is aimed at establishing the suitability of these voice spectral parameters in fixing a clear distinction between pathologic and normophonic voice, and to further classify the specific patient's pathology. Principal component analysis is used in parameter selection. Results for normal and pathological samples will be presented and discussed.
京公网安备 11010802042870号
京ICP备2023020795号-1
分享
求助内容：
应助结果提醒方式：
扫码关注我们
