Abstract
Our aim is to build a real-time Embodied Conversational Agent able to act as an interlocutor in interaction, generating automatically verbal and non verbal signals. These signals, called backchannels, provide information about the listener’s mental state towards the perceived speech. The ECA reacts differently to user’s behavior depending on its predefined personality. Personality influences the generation and the selection of backchannels. In this paper, we propose a listener’s action selection algorithm working in real-time to choose the type and the frequency of backchannels to be displayed by the ECA in accordance with its personality. The algorithm is based on the extroversion and neuroticism dimensions of personality. We present an evaluation on how backchanels managed by this algorithm are congruent with intuitive expectations of participants in terms of behavior specific to different personalities.
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de Sevin, E., Hyniewska, S.J., Pelachaud, C. (2010). Influence of Personality Traits on Backchannel Selection. In: Allbeck, J., Badler, N., Bickmore, T., Pelachaud, C., Safonova, A. (eds) Intelligent Virtual Agents. IVA 2010. Lecture Notes in Computer Science(), vol 6356. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15892-6_20
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DOI: https://doi.org/10.1007/978-3-642-15892-6_20
Publisher Name: Springer, Berlin, Heidelberg
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