Generating Challenge Datasets for Task-Oriented Conversational Agents through Self-Play

RANLP 2019 Sourabh MajumdarSerra Sinem TekirogluMarco Guerini

End-to-end neural approaches are becoming increasingly common in conversational scenarios due to their promising performances when provided with sufficient amount of data. In this paper, we present a novel methodology to address the interpretability of neural approaches in such scenarios by creating challenge datasets using dialogue self-play over multiple tasks/intents... (read more)

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