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Context-Aware Automated Analysis and Annotation of Social Human-Agent Interactions

Tobias Baur, Gregor Mehlmann, Ionut Damian, Patrick Gebhard, Florian Lingenfelser, Johannes Wagner, Birgit Lugrin, and Elisabeth André

Context-Aware Automated Analysis and Annotation of Social Human-Agent Interactions

The outcome of interpersonal interactions depends not only on the contents that we communicate verbally but also on nonverbal social signals...

erschienen in press ACM Transactions on Interactive Intelligent Systems 5.2

Verlag: ACM


The outcome of interpersonal interactions depends not only on the contents that we communicate verbally but also on nonverbal social signals. As a lack of social skills is a common problem for a significant number of people, serious games and other training environments have recently become the focus of research. In this work we present NovA (Nonverbal behaviour Analyzer), a system that analyzes and facilitates the interpretation of social signals automatically in a bi-directional interaction with a conversational agent. It records data of interactions, detects relevant social cues, and creates descriptive statistics for the recorded data with respect to the agent s behavior and the context of the situation. This enhances the possibilities for researchers to automatically label corpora of human-agent interactions and to give users feedback on strengths and weaknesses of their social behavior.