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Autoencoder를 이용한 음성 신호 기반의 연하장애 검출 기법

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dc.contributor.author박윤길-
dc.contributor.author박진영-
dc.date.accessioned2023-04-07T01:09:35Z-
dc.date.available2023-04-07T01:09:35Z-
dc.date.issued2022-02-
dc.identifier.issn1976-7102-
dc.identifier.urihttps://ir.ymlib.yonsei.ac.kr/handle/22282913/193780-
dc.description.abstractn this paper, a novel approach is proposed to improve speech-based dysphagia detection using an autoencoder. The water swallow test using voice is a convenient test method but has a problem due to low accuracy. Based on the /a/ voice data before and after the VFSS(Video Fluoroscopic Swallowing Study) test, which is a representative method for examining dysphagia, an autoencoder with a strong performance in detecting abnormalities is used to determine dysphagia. Data from 33 normal subjects were used for training. In 16 normal subjects and 39 patients with dysphagia, the proposed algorithm yields 23%p higher performance compared with the conventional Praat based scheme.-
dc.description.statementOfResponsibilityrestriction-
dc.languageKorean-
dc.publisher한국재활복지공학회-
dc.relation.isPartOfJournal of Rehabilitation Welfare Engineering & Assistive Technology(재활복지공학회논문지)-
dc.rightsCC BY-NC-ND 2.0 KR-
dc.titleAutoencoder를 이용한 음성 신호 기반의 연하장애 검출 기법-
dc.title.alternativeSpeech Signal based Dysphagia Detection using Autoencoder-
dc.typeArticle-
dc.contributor.collegeCollege of Medicine (의과대학)-
dc.contributor.departmentDept. of Rehabilitation Medicine (재활의학교실)-
dc.contributor.googleauthor강상익-
dc.contributor.googleauthor조경일-
dc.contributor.googleauthor금명철-
dc.contributor.googleauthor서경천-
dc.contributor.googleauthor박윤길-
dc.contributor.googleauthor박진영-
dc.contributor.googleauthor차은실-
dc.contributor.googleauthor정석영-
dc.contributor.googleauthor이주강-
dc.contributor.googleauthor유제현-
dc.contributor.googleauthor최경효-
dc.identifier.doi10.21288/resko.2022.16.1.13-
dc.contributor.localIdA01596-
dc.contributor.localIdA04941-
dc.relation.journalcodeJ01734-
dc.identifier.urlhttps://www.dbpia.co.kr/journal/articleDetail?nodeId=NODE11038948-
dc.subject.keywordDysphagia-
dc.subject.keywordAutoencoder-
dc.subject.keywordAnomaly detection-
dc.subject.keywordVFSS-
dc.subject.keywordVoice-based diagnosis-
dc.contributor.alternativeNamePark, Yoon Ghil-
dc.contributor.affiliatedAuthor박윤길-
dc.contributor.affiliatedAuthor박진영-
dc.citation.volume16-
dc.citation.number1-
dc.citation.startPage13-
dc.citation.endPage18-
dc.identifier.bibliographicCitationJournal of Rehabilitation Welfare Engineering & Assistive Technology(재활복지공학회논문지), Vol.16(1) : 13-18, 2022-02-
Appears in Collections:
1. College of Medicine (의과대학) > Dept. of Rehabilitation Medicine (재활의학교실) > 1. Journal Papers

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