DocumentCode
3703357
Title
Automatic personality perception: Prediction of trait attribution based on prosodic features extended abstract
Author
Gelareh Mohammadi;Alessandro Vinciarelli
Author_Institution
Department of Neuroscience, University of Geneva, Switzerland
fYear
2015
Firstpage
484
Lastpage
490
Abstract
This paper proposes a prosody based approach for Automatic Personality Perception. Social psychology has shown that whenever we listen to a voice for the first time, we spontaneously and unconsciously attribute personality traits to the speaker. The attribution process is not necessarily accurate, but it is important because it shapes our behavior towards others. The experiments of this work are performed over a corpus of 640 speech samples (322 individuals in total) assessed in terms of speaker´s personality traits by 11 judges. The results show that it is possible to predict some of the personality traits with accuracy higher than 70%. The effect of different prosodic features has also been analyzed and compared with findings in the psychological literature.
Keywords
"Feature extraction","Speech","Psychology","Entropy","Logistics","Speech processing","Neuroscience"
Publisher
ieee
Conference_Titel
Affective Computing and Intelligent Interaction (ACII), 2015 International Conference on
Electronic_ISBN
2156-8111
Type
conf
DOI
10.1109/ACII.2015.7344614
Filename
7344614
Link To Document