Atasoy, HuseyinYildirim, SerdarYildirim, Esen2024-09-182024-09-182015978-1-4673-7386-92165-0608https://hdl.handle.net/20.500.12483/1183823nd Signal Processing and Communications Applications Conference (SIU) -- MAY 16-19, 2015 -- Inonu Univ, Malatya, TURKEYIn this study, a large number of features that were obtained to classify speech emotions were projected into different spaces, selecting different numbers of principal components in principal component analysis and Fisher's discriminant analysis. Classifications were performed in those spaces using Naive-Bayes classifier and obtained results were compared. While the highest accuracy obtained in the Fisher space was 57.87%, it was calculated as 48.02% in the principal component space.trinfo:eu-repo/semantics/closedAccessprincipal component analysisfisher's linear discriminant analysisemotion recognitionConference Object251325162-s2.0-84939168699N/AWOS:000380500900612N/A