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음성신호를 이용한 감성인식에서의 패턴인식 방법

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dc.contributor.author박창현-
dc.contributor.author심귀보-
dc.date.available2019-07-18T03:58:19Z-
dc.date.issued2006-
dc.identifier.issn1976-5622-
dc.identifier.urihttps://scholarworks.bwise.kr/cau/handle/2019.sw.cau/29203-
dc.description.abstractIn this paper, we apply several pattern recognition algorithms to emotion recognition system with speech signal and compare the results. Firstly, we need emotional speech databases. Also, speech features for emotion recognition is determined on the database analysis step. Secondly, recognition algorithms are applied to these speech features. The algorithms we try are artificial neural network, Bayesian learning, Principal Component Analysis, LBG algorithm. Thereafter, the performance gap of these methods is presented on the experiment result section. Truly, emotion recognition technique is not mature. That is, the emotion feature selection, relevant classification method selection, all these problems are disputable. So, we wish this paper to be a reference for the disputes.-
dc.format.extent5-
dc.publisher제어·로봇·시스템학회-
dc.title음성신호를 이용한 감성인식에서의 패턴인식 방법-
dc.title.alternativeThe Pattern Recognition Methods for Emotion Recognitionwith Speech Signal-
dc.typeArticle-
dc.identifier.bibliographicCitation제어.로봇.시스템학회 논문지, v.12, no.3, pp 284 - 288-
dc.identifier.kciidART000995974-
dc.description.isOpenAccessN-
dc.citation.endPage288-
dc.citation.number3-
dc.citation.startPage284-
dc.citation.title제어.로봇.시스템학회 논문지-
dc.citation.volume12-
dc.publisher.location대한민국-
dc.subject.keywordAuthoremotion recognition-
dc.subject.keywordAuthorANN-
dc.subject.keywordAuthorbayesian learning-
dc.subject.keywordAuthorprincipal component analysis-
dc.subject.keywordAuthorLBG algorithm-
dc.description.journalRegisteredClasskci-
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