Abstract
In SAIBA-compliant agent systems, the Function Markup Language (FML) is used to describe the agent’s communicative functions that are transformed into utterances accompanied with appropriate non-verbal behaviours. In the context of the ARIA Framework, we propose a template-based approach, grounded in the DIT++ taxonomy, as an interface between the dialogue manager (DM) and the non-verbal behaviour generation (NVBG) components of this framework. Our approach enhances our current FML-APML implementation of FML with the capability of receiving on-the-fly generated natural language and socio-emotional parameters (e.g. emotional stance) for transforming the agent’s intents in believable verbal and non-verbal behaviours in an adaptive manner.
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Cafaro, A., Bruijnes, M., van Waterschoot, J., Pelachaud, C., Theune, M., Heylen, D. (2017). Selecting and Expressing Communicative Functions in a SAIBA-Compliant Agent Framework. In: Beskow, J., Peters, C., Castellano, G., O'Sullivan, C., Leite, I., Kopp, S. (eds) Intelligent Virtual Agents. IVA 2017. Lecture Notes in Computer Science(), vol 10498. Springer, Cham. https://doi.org/10.1007/978-3-319-67401-8_8
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DOI: https://doi.org/10.1007/978-3-319-67401-8_8
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