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Dealing with Trouble: A Data-Driven Model of a Repair Type for a Conversational Agent
Last modified: 2015-03-04
Abstract
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.
Keywords
Linguistic Repair in Chat, Conversational Agents, Second Language Acquisition
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