New feature selection frameworks in emotion recognition to evaluate the informative power of speech related features

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dc.authorid0000-0002-2126-8757
dc.contributor.authorAltun, H.
dc.contributor.authorShawe-Taylor, J.
dc.contributor.authorPolat, G.
dc.date.accessioned2019-08-01T13:38:39Z
dc.date.available2019-08-01T13:38:39Z
dc.date.issued2007
dc.departmentNiğde ÖHÜ
dc.description9th International Symposium on Signal Processing and its Applications -- FEB 12-15, 2007 -- Sharjah, U ARAB EMIRATES
dc.description.abstractIn this paper, we propose two new frameworks, so as to boost the feature selection algorithms in a way that the selected features will be more informative in terms of class-separability. In the first framework, features that are more informative in discriminating an emotional class from the rest of the classes are favoured for selection by the feature selection algorithms. In the second framework features that more informative in terms of separating an emotional class from another one are favoured for selection. Then, final feature subsets are constructed from the subsets of selected features using intersection and unification operators. It will be shown that the proposed frameworks fulfill the objectives by considerably reducing average cross-validation error.
dc.description.sponsorshipTUBITAK (The Scientific and Technological Research Council of Turkey); TUBITAK Project [104E179]
dc.description.sponsorshipThis work has been partly supported by TUBITAK (The Scientific and Technological Research Council of Turkey) Grant offered to Dr. Altun during his stay as a visiting researcher at University of Southampton and at University College of London. This work has also been partly sponsored by TUBITAK Project under the contract of 104E179.
dc.identifier.endpage+
dc.identifier.isbn978-1-4244-0778-1
dc.identifier.scopus2-s2.0-51549090471
dc.identifier.scopusqualityN/A
dc.identifier.startpage564
dc.identifier.urihttps://hdl.handle.net/11480/5418
dc.identifier.wosWOS:000259439900142
dc.identifier.wosqualityN/A
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.institutionauthor[0-Belirlenecek]
dc.language.isoen
dc.publisherIEEE
dc.relation.ispartof2007 9TH INTERNATIONAL SYMPOSIUM ON SIGNAL PROCESSING AND ITS APPLICATIONS, VOLS 1-3
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.titleNew feature selection frameworks in emotion recognition to evaluate the informative power of speech related features
dc.typeConference Object

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