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 features on a dataset of adults interacting with the iCub robot show the effectiveness of this approach.
This paper introduces an automatic system for the prediction of extraversion during the rst 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 features on a dataset of adults interacting with the iCub robot show the e ectiveness of this approach.
Automated Prediction of Extraversion during Human-Robot Interaction / Anzalone, Salvatore M.; Varni, Giovanna; Zibetti, Elisabetta; Ivaldi, Serena; Chetouani, Mohamed. - 1544:(2015), pp. 29-39. ( 2nd Italian Workshop on Artificial Intelligence and Robotics, AIRO 2015 Ferrara 22 settembre 2015).
Automated Prediction of Extraversion during Human-Robot Interaction
Giovanna Varni;
2015-01-01
Abstract
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 features on a dataset of adults interacting with the iCub robot show the effectiveness of this approach.| File | Dimensione | Formato | |
|---|---|---|---|
|
paper3.pdf
accesso aperto
Tipologia:
Versione editoriale (Publisher’s layout)
Licenza:
Tutti i diritti riservati (All rights reserved)
Dimensione
866.47 kB
Formato
Adobe PDF
|
866.47 kB | Adobe PDF | Visualizza/Apri |
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione



