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

Context-Aware Automated Analysis and Annotation of Social Human--Agent Interactions Context-Aware Automated Analysis and Annotation of Social Human­Agent Interactions TOBIAS BAUR, GREGOR MEHLMANN, IONUT DAMIAN, FLORIAN LINGENFELSER, ´ JOHANNES WAGNER, BIRGIT LUGRIN, and ELISABETH ANDRE, Augsburg University PATRICK GEBHARD, DFKI GmbH The outcome of interpersonal interactions depends not only on the contents that we communicate verbally, but also on nonverbal social signals. Because 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 behavior Analyzer), a system that analyzes and facilitates the interpretation of social signals automatically in a bidirectional 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 human­agent interactions and to give users feedback on strengths and weaknesses of their social behavior. Categories and Subject Descriptors: H.1.2 [User/Machine Systems]: Human Information Processing General Terms: Social Signal Processing, Serious Games, Virtual Agents, Affective Computing Additional Key Words and Phrases: Social cue recognition, virtual job interviews, serious http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png ACM Transactions on Interactive Intelligent Systems (TiiS) Association for Computing Machinery

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Publisher
Association for Computing Machinery
Copyright
Copyright © 2015 by ACM Inc.
ISSN
2160-6455
DOI
10.1145/2764921
Publisher site
See Article on Publisher Site

Abstract

Context-Aware Automated Analysis and Annotation of Social Human­Agent Interactions TOBIAS BAUR, GREGOR MEHLMANN, IONUT DAMIAN, FLORIAN LINGENFELSER, ´ JOHANNES WAGNER, BIRGIT LUGRIN, and ELISABETH ANDRE, Augsburg University PATRICK GEBHARD, DFKI GmbH The outcome of interpersonal interactions depends not only on the contents that we communicate verbally, but also on nonverbal social signals. Because 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 behavior Analyzer), a system that analyzes and facilitates the interpretation of social signals automatically in a bidirectional 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 human­agent interactions and to give users feedback on strengths and weaknesses of their social behavior. Categories and Subject Descriptors: H.1.2 [User/Machine Systems]: Human Information Processing General Terms: Social Signal Processing, Serious Games, Virtual Agents, Affective Computing Additional Key Words and Phrases: Social cue recognition, virtual job interviews, serious

Journal

ACM Transactions on Interactive Intelligent Systems (TiiS)Association for Computing Machinery

Published: Jun 30, 2015

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