피처벡터 축소방법에 기반한 장애음성 분류Classification of pathological and normal voice based on dimension reduction of feature vectors

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dc.contributor.author이, 지연-
dc.contributor.author정, 상배-
dc.contributor.author최, 홍식-
dc.contributor.author한, 민수-
dc.contributor.authorLee, Ji-Yeoun-
dc.contributor.authorJeong, Sang-Bae-
dc.contributor.authorChoi, Hong-Shik-
dc.contributor.authorHahn, Min-Soo-
dc.date.accessioned2011-11-08T04:24:29Z-
dc.date.available2011-11-08T04:24:29Z-
dc.date.issued2007-05-
dc.identifier.citation대한음성학회 학술대회논문집en
dc.identifier.urihttp://hdl.handle.net/10203/25522-
dc.description.abstractThis paper suggests a method to improve the performance of the pathological/normal voice classification. The effectiveness of the mel frequency-based filter bank energies using the fisher discriminant ratio (FDR) is analyzed. And mel frequency cepstrum coefficients (MFCCs) and the feature vectors through the linear discriminant analysis (LDA) transformation of the filter bank energies (FBE) are implemented. This paper shows that the FBE LDA-based GMM is more distinct method for the pathological/normal voice classification than the MFCC-based GMM.en
dc.language.isokoen
dc.publisher대한음성학회en
dc.title피처벡터 축소방법에 기반한 장애음성 분류en
dc.title.alternativeClassification of pathological and normal voice based on dimension reduction of feature vectorsen
dc.typeBooken

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