Dealing with Trouble: A Data-Driven Model of a Repair Type for a Conversational Agent
DOI:
https://doi.org/10.1609/aaai.v29i1.9724Keywords:
Linguistic Repair in Chat, Conversational Agents, Second Language AcquisitionAbstract
Troubles in hearing, comprehension or speech production are common in human conversations, especially if participants of the conversation communicate in a foreign language that they have not yet fully mastered. Here I describe a data-driven model for simulation of dialogue sequences where the learner user does not understand the talk of a conversational agent in chat and asks for clarification.
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Published
2015-03-04
How to Cite
Höhn, S. (2015). Dealing with Trouble: A Data-Driven Model of a Repair Type for a Conversational Agent. Proceedings of the AAAI Conference on Artificial Intelligence, 29(1). https://doi.org/10.1609/aaai.v29i1.9724
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Student Abstract Track