Co-constructing Grounded Symbols—Feedback and Incremental Adaptation in Human–Agent Dialogue
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Grounding in dialogue concerns the question of how the gap between the individual symbol systems of interlocutors can be bridged so that mutual understanding is possible. This problem is highly relevant to human–agent interaction where mis- or non-understanding is common. We argue that humans minimise this gap by collaboratively and iteratively creating a shared conceptualisation that serves as a basis for negotiating symbol meaning. We then present a computational model that enables an artificial conversational agent to estimate the user’s mental state (in terms of contact, perception, understanding, acceptance, agreement and based upon his or her feedback signals) and use this information to incrementally adapt its ongoing communicative actions to the user’s needs. These basic abilities are important to reduce friction in the iterative coordination process of co-constructing grounded symbols in dialogue.
KeywordsSymbol grounding Dialogue Feedback Adaptation Human-agent Interaction
This research is supported by the Deutsche Forschungsgemeinschaft (DFG) in the Center of Excellence EXC 277 in ‘Cognitive Interaction Technology’ (CITEC).
- 5.Buschmeier H, Baumann T, Dosch B, Kopp S, Schlangen D (2012) Combining incremental language generation and incremental speech synthesis for adaptive information presentation. In: Proceedings of the 13th Annual Meeting of the Special Interest Group on Discourse and Dialogue, Seoul, South Korea, pp 295–303 Google Scholar
- 7.Buschmeier H, Kopp S (2012) Using a Bayesian model of the listener to unveil the dialogue information state. In: SemDial 2012: Proceedings of the 16th Workshop on the Semantics and Pragmatics of Dialogue, Paris, France, pp 12–20 Google Scholar
- 8.Chao YR (1968) Language and symbolic systems. Cambridge University Press, Cambridge Google Scholar
- 14.Grice HP (1975) Logic and conversation. In: Cole P, Morgan JL (eds) Syntax and semantics 3: Speech acts. Academic Press, New York, pp 41–58 Google Scholar
- 16.Heldner M, Edlund J, Hirschberg J (2010) Pitch similarity in the vicinity of backchannels. In: Proceedings of INTERSPEECH 2010. Makuhari, Japan, pp 3054–3057 Google Scholar
- 17.de Kok I, Heylen D (2011) The MultiLis corpus – Dealing with individual differences in nonverbal listening behavior. In: Proceedings of the 3rd COST 2102 International Training School, Caserta, Italy, pp 362–375 Google Scholar
- 18.de Kok I, Ozkan D, Heylen D, Morency LP (2010) Learning and evaluating response prediction models using parallel listener consensus. In: Proceedings of the 12th International Conference on Multimodal Interfaces, Beijing, China Google Scholar