Abstract
How does a virtual agent’s gesturing behavior influence the user’s perception of communication quality and the agent’s personality? This question was investigated in an evaluation study of co-verbal iconic gestures produced with the Bayesian network-based production model GNetIc. A network learned from a corpus of several speakers was compared with networks learned from individual speaker data, as well as two control conditions. Results showed that automatically GNetIc-generated gestures increased the perceived quality of an object description given by a virtual human. Moreover, gesturing behavior generated with individual speaker networks was rated more positively in terms of likeability, competence and human-likeness.
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Bergmann, K., Kopp, S., Eyssel, F. (2010). Individualized Gesturing Outperforms Average Gesturing – Evaluating Gesture Production in Virtual Humans. 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_11
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DOI: https://doi.org/10.1007/978-3-642-15892-6_11
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