By Topic

Automatic Personality Perception: Prediction of Trait Attribution Based on Prosodic Features

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Mohammadi, G. ; IDIAP Res. Inst., Martigny, Switzerland ; Vinciarelli, A.

Whenever we listen to a voice for the first time, we attribute personality traits to the speaker. The process takes place in a few seconds and it is spontaneous and unaware. While the process is not necessarily accurate (attributed traits do not necessarily correspond to the actual traits of the speaker), still it significantly influences our behavior toward others, especially when it comes to social interaction. This paper proposes an approach for the automatic prediction of the traits the listeners attribute to a speaker they never heard before. The experiments are performed over a corpus of 640 speech clips (322 identities in total) annotated in terms of personality traits by 11 assessors. The results show that it is possible to predict with high accuracy (more than 70 percent depending on the particular trait) whether a person is perceived to be in the upper or lower part of the scales corresponding to each of the Big -Five, the personality dimensions known to capture most of the individual differences.

Published in:

Affective Computing, IEEE Transactions on  (Volume:3 ,  Issue: 3 )