Title | Detecting User Engagement with a Robot Companion Using Task and Social Interaction-based Features |
Publication Type | Conference Paper |
Year of Publication | 2009 |
Authors | Castellano G, Pereira A, Leite I, Paiva A, McOwan PW |
Conference Name | ACM International Conference on Multimodal Interfaces |
Publisher | ACM |
Conference Location | Cambridge, MA |
Keywords | affect recognition, contextual information, human-robot interaction, lirec, non-verbal expressive behaviour |
Abstract | Affect sensitivity is of the utmost importance for a robot
companion to be able to display socially intelligent behaviour,
a key requirement for sustaining long-term interactions with
humans. This paper explores a naturalistic scenario in which
children play chess with the iCat, a robot companion. A
person-independent, Bayesian approach to detect the user's
engagement with the iCat robot is presented. Our frame-
work models both causes and effects of engagement: features
related to the user's non-verbal behaviour, the task and the
companion's affective reactions are identified to predict the
children's level of engagement. An experiment was carried
out to train and validate our model. Results show that our
approach based on multimodal integration of task and social
interaction-based features outperforms those based solely on
non-verbal behaviour or contextual information (94.79 % vs.
93.75% and 78.13%). |
URL | http://dl.lirec.org/papers/CastellanoEtAl_ICMI2009.pdf |