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Detecting Inappropriate Clarification Requests in Spoken Dialogue Systems

Liu, Alex; Sloan, Rose; Then, Mei-Vern; Stoyanchev, Svetlana; Hirschberg, Julia Bell; Shriberg, Elizabeth

Spoken Dialogue Systems ask for clarification when they think they have misunderstood users. Such requests may differ depending on the information the system believes it needs to clarify. However, when the error type or location is misidentified, clarification requests appear confusing or inappropriate. We describe a classifier that identifies inappropriate requests, trained on features extracted from user responses in laboratory studies. This classifier achieves 88.5% accuracy and .885 F-measure in detecting such requests.

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Also Published In

Title
Proceedings of the 15th Annual Meeting of the Special Interest Group on Discourse and Dialogue (SIGDIAL)

More About This Work

Academic Units
Computer Science
Published Here
November 11, 2014