{"title":"Pathological voice recognition by deep neural network","authors":"Xiaojun Zhang, Zhi Tao, Heming Zhao, Tianqi Xu","doi":"10.1109/ICSAI.2017.8248337","DOIUrl":null,"url":null,"abstract":"The deep neural network(DNN) is used for the identification and classification of pathological voice. Time domain characteristics and frequency domain characteristics are selected. Compared with the traditional recognition algorithm. The result of experimental shows that the DNN method can effectively improve the recognition rate in both normal-pathological voice of vocal cords recognition and pathological voice of vocal cords segmentation.","PeriodicalId":285726,"journal":{"name":"2017 4th International Conference on Systems and Informatics (ICSAI)","volume":"3 11 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 4th International Conference on Systems and Informatics (ICSAI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSAI.2017.8248337","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
The deep neural network(DNN) is used for the identification and classification of pathological voice. Time domain characteristics and frequency domain characteristics are selected. Compared with the traditional recognition algorithm. The result of experimental shows that the DNN method can effectively improve the recognition rate in both normal-pathological voice of vocal cords recognition and pathological voice of vocal cords segmentation.
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