H. Aydan, Meral Korkmaz, Beyza Cizmeci, I. Koçak, Nilufer Egrican, G. Ince
{"title":"Voice cloud platform for medical applications","authors":"H. Aydan, Meral Korkmaz, Beyza Cizmeci, I. Koçak, Nilufer Egrican, G. Ince","doi":"10.1109/SIU.2017.7960685","DOIUrl":null,"url":null,"abstract":"The usability and health of a person's voice has dire impact on the person's quality of life. Pathological issues that may exist on a person's voice often cannot be detected by a regular listener. Medical attention from a professional may be necessary to detect vocal pathologies. Analysis of the patients complaints and a perceptual evaluation performed by a doctor is one of the most common ways to diagnose a vocal condition. This method can be invasive, time consuming and expensive. Features of the voice can be extracted and utilized in a computer environment to make the same diagnosis which may increase the speed and accuracy of the diagnosis and decrease the cost. In this paper, a cloud application which collects vocal data in a database is proposed. With data mining and machine learning methods, a new tool has been developed to detect and diagnose vocal anomalies in patients. The effectiveness of the suggested platform has been demonstrated with a pathological detection and recognition application running in the server.","PeriodicalId":217576,"journal":{"name":"2017 25th Signal Processing and Communications Applications Conference (SIU)","volume":"88 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 25th Signal Processing and Communications Applications Conference (SIU)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SIU.2017.7960685","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The usability and health of a person's voice has dire impact on the person's quality of life. Pathological issues that may exist on a person's voice often cannot be detected by a regular listener. Medical attention from a professional may be necessary to detect vocal pathologies. Analysis of the patients complaints and a perceptual evaluation performed by a doctor is one of the most common ways to diagnose a vocal condition. This method can be invasive, time consuming and expensive. Features of the voice can be extracted and utilized in a computer environment to make the same diagnosis which may increase the speed and accuracy of the diagnosis and decrease the cost. In this paper, a cloud application which collects vocal data in a database is proposed. With data mining and machine learning methods, a new tool has been developed to detect and diagnose vocal anomalies in patients. The effectiveness of the suggested platform has been demonstrated with a pathological detection and recognition application running in the server.