Year: 2012
Type: article
Abstract: 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 influences significantly our behavior towards others, especially when it comes to social interaction.This article 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% 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.
Authors: Gelareh Mohammadi, Alessandro Vinciarelli
Language: English
Topic: Emotion and Mood Recognition
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W656799717