Abstract
This demo presents an approach to recognising and interpreting social cues-based interactions in computer-enhanced job interview simulations. We show what social cues and complex mental states of the user are relevant in this interaction context, how they can be interpreted using static Bayesian Networks, and how they can be recognised automatically using state-of-the-art sensor technology in real-time.
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Porayska-Pomsta, K. et al. (2013). Modelling Users’ Affect in Job Interviews: Technological Demo. In: Carberry, S., Weibelzahl, S., Micarelli, A., Semeraro, G. (eds) User Modeling, Adaptation, and Personalization. UMAP 2013. Lecture Notes in Computer Science, vol 7899. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38844-6_37
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DOI: https://doi.org/10.1007/978-3-642-38844-6_37
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-38843-9
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