Emotion recognition from speech using Fisher's discriminant analysis and Bayesian classifier Fisher Ayrişim Analizi ve Bayes Siniflandirici ile Sesten Duygu Tanima

Atasoy H., Yildirim S., Yildirim E.

2015 23rd Signal Processing and Communications Applications Conference, SIU 2015, Malatya, Turkey, 16 - 19 May 2015, pp.2513-2516, (Full Text) identifier identifier

  • Publication Type: Conference Paper / Full Text
  • Doi Number: 10.1109/siu.2015.7130395
  • City: Malatya
  • Country: Turkey
  • Page Numbers: pp.2513-2516
  • Keywords: emotion recognition, fisher's linear discriminant analysis, principal component analysis
  • Hatay Mustafa Kemal University Affiliated: Yes

Abstract

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 Naïve-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.