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Detecting User Engagement with a Robot Companion Using Task and Social Interaction-based Features

TitleDetecting User Engagement with a Robot Companion Using Task and Social Interaction-based Features
Publication TypeConference Paper
Year of Publication2009
AuthorsCastellano G, Pereira A, Leite I, Paiva A, McOwan PW
Conference NameACM International Conference on Multimodal Interfaces
PublisherACM
Conference LocationCambridge, MA
Keywordsaffect recognition, contextual information, human-robot interaction, lirec, non-verbal expressive behaviour
AbstractAffect 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%).
URLhttp://dl.lirec.org/papers/CastellanoEtAl_ICMI2009.pdf
Posted by Ginevra on Friday, 23 October, 2009 /
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