Comparing categorical and dimensional ratings of emotional speech

Noam Amir, Reut Rubinstein, Adi Shlomov, Gary Diamond

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

- the purpose of this study was to examine how the judgments of several emotional categories map onto the ArousalValence emotional space, and how this mapping is influenced by the intensity of these emotions. 20 judges were asked to rate excerpts of emotional speech taken from corpora of acted and elicited emotional speech, using two methods: 1) categorical labeling; and 2) 5-point scales representing Arousal and Valence. Results showed the commonly used negative emotions (Anger Sadness and Fear) to have large degree of overlap, though their centroids were distinct. When the centroids were plotted as a function of emotional intensity, they formed relatively straight lines pointing roughly to Neutral. However, in contrast to assumptions in the literature, Neutral was found to center around a negative value of arousal. Thus the entire emotional space was somewhat biased in the direction of negative arousal. Overall, the variability in judgment of Arousal was found to be large in comparison to the variability in Valence.

Original languageEnglish
Title of host publication2015 11th IEEE International Conference and Workshops on Automatic Face and Gesture Recognition, FG 2015
PublisherInstitute of Electrical and Electronics Engineers
ISBN (Electronic)9781479960262
DOIs
StatePublished - 17 Jul 2015
Event11th IEEE International Conference and Workshops on Automatic Face and Gesture Recognition, FG 2015 - Ljubljana, Slovenia
Duration: 4 May 20158 May 2015

Publication series

Name2015 11th IEEE International Conference and Workshops on Automatic Face and Gesture Recognition, FG 2015
Volume2015-January

Conference

Conference11th IEEE International Conference and Workshops on Automatic Face and Gesture Recognition, FG 2015
Country/TerritorySlovenia
CityLjubljana
Period4/05/158/05/15

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition

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