Chollet, M. , Ochs, M. and Pelachaud, C. (2014) From non-verbal signals sequence mining to bayesian networks for interpersonal attitudes expression. In: Bickmore, T., Marsella, S. and Sidner, C. (eds.) Intelligent Virtual Agents: 14th International Conference, IVA 2014, Boston, MA, USA, August 27-29, 2014, Proceedings. Series: Lecture notes in computer science. Springer, pp. 120-133. ISBN 9783319097671 (doi: 10.1007/978-3-319-09767-1_15)
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Abstract
In this paper, we present a model and its evaluation for expressing attitudes through sequences of non-verbal signals for Embodied Conversational Agents. To build our model, a corpus of job interviews has been annotated at two levels: the non-verbal behavior of the recruiters as well as their expressed attitudes was annotated. Using a sequence mining method, sequences of non-verbal signals characterizing different interpersonal attitudes were automatically extracted from the corpus. From this data, a probabilistic graphical model was built. The probabilistic model is used to select the most appropriate sequences of non-verbal signals that an ECA should display to convey a particular attitude. The results of a perceptive evaluation of sequences generated by the model show that such a model can be used to express interpersonal attitudes.
| Item Type: | Book Sections |
|---|---|
| Additional Information: | This research has been partially supported by the European Community Seventh Framework Program (FP7/2007-2013), under grant agreement no. 288578 (TARDIS). |
| Status: | Published |
| Glasgow Author(s) Enlighten ID: | Chollet, Dr Mathieu |
| Authors: | Chollet, M., Ochs, M., and Pelachaud, C. |
| College/School: | College of Science and Engineering > School of Computing Science |
| Journal Name: | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
| Publisher: | Springer |
| ISBN: | 9783319097671 |
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