Predicting Extraversion from Non-verbal Features During a Face-to-Face Human-Robot Interaction
نویسندگان
چکیده
In this paper we present a system for automatic prediction of extraversion during the first thin slices of human-robot interaction (HRI). This work is based on the hypothesis that personality traits and attitude towards robot appear in the behavioural response of humans during HRI. We propose a set of four non-verbal movement features that characterize human behavior during interaction. We focus our study on predicting Extraversion using these features, extracted from a dataset consisting of 39 healthy adults interacting with the humanoid iCub. Our analysis shows that it is possible to predict to a good level (64%) the Extraversion of a human from a thin slice of interaction relying only on non-verbal movement features. Our results are comparable to the state-of-the-art obtained in HHI [23].
منابع مشابه
Automated Prediction of Extraversion during Human-Robot Interaction
This paper introduces an automatic system for the prediction of extraversion during the first minutes interaction between humans and and a humanoid robot. In such interactions the behavioural response of people depends by their personality traits and by their attitude towards robots. A set of non-verbal features is proposed to characterize such behavioural responses. Results obtained using such...
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