New feature selection frameworks in emotion recognition to evaluate the informative power of speech related features
Küçük Resim Yok
Tarih
2007
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
IEEE
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
In 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.
Açıklama
9th International Symposium on Signal Processing and its Applications -- FEB 12-15, 2007 -- Sharjah, U ARAB EMIRATES
Anahtar Kelimeler
Kaynak
2007 9TH INTERNATIONAL SYMPOSIUM ON SIGNAL PROCESSING AND ITS APPLICATIONS, VOLS 1-3
WoS Q Değeri
N/A
Scopus Q Değeri
N/A
