Emotion Recognition From Speech Using Fisher's Discriminant Analysis and Bayesian Classifier

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Tarih

2015

Dergi Başlığı

Dergi ISSN

Cilt Başlığı

Yayıncı

Ieee

Erişim Hakkı

info:eu-repo/semantics/closedAccess

Özet

In 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.

Açıklama

23nd Signal Processing and Communications Applications Conference (SIU) -- MAY 16-19, 2015 -- Inonu Univ, Malatya, TURKEY

Anahtar Kelimeler

principal component analysis, fisher's linear discriminant analysis, emotion recognition

Kaynak

2015 23rd Signal Processing and Communications Applications Conference (Siu)

WoS Q Değeri

N/A

Scopus Q Değeri

N/A

Cilt

Sayı

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