%0 Journal Article
%T Emotion Recognition and Emotion Spotting Improvement Using Formant-Related Features
%A Davood Gharavian
%A Mansour Sheikhan
%J Majlesi Journal of Electrical Engineering
%D 2010
%I Islamic Azad University- Majlesi
%R 10.1234/mjee.v4i4.266
%X Emotion has an important role in naturalness of man-machine communication. So, computerized emotion recognition from speech is investigated by many researchers in the recent decades. In this paper, the effect of formant-related features on improving the performance of emotion detection systems is experimented. To do this, various forms and combinations of the first three formants are concatenated to a popular feature vector and Gaussian mixture models are used as classifiers. Experimental results show average recognition rate of 69% in four emotional states and noticeable performance improvement by adding only one formant-related parameter to feature vector. The architecture of hybrid emotion recognition/spotting is also proposed based on the developed models.
%K Emotion recognition
%K formants
%K Gaussian mixture model
%U http://ee.majlesi.info/index/index.php/ee/article/view/266