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Automatic Detection of Miscommunication in Spoken Dialogue Systems
KTH, School of Computer Science and Communication (CSC), Speech, Music and Hearing, TMH, Speech Communication and Technology.ORCID iD: 0000-0002-7412-0967
KTH, School of Computer Science and Communication (CSC), Speech, Music and Hearing, TMH.ORCID iD: 0000-0002-8773-9216
KTH, School of Computer Science and Communication (CSC), Speech, Music and Hearing, TMH, Speech Communication and Technology.ORCID iD: 0000-0002-8579-1790
KTH, School of Computer Science and Communication (CSC), Speech, Music and Hearing, TMH, Speech Communication and Technology.ORCID iD: 0000-0002-0397-6442
2015 (English)In: Proceedings of 16th Annual Meeting of the Special Interest Group on Discourse and Dialogue (SIGDIAL), 2015, 354-363 p.Conference paper (Refereed)
Abstract [en]

In this paper, we present a data-driven approach for detecting instances of miscommunication in dialogue system interactions. A range of generic features that are both automatically extractable and manually annotated were used to train two models for online detection and one for offline analysis. Online detection could be used to raise the error awareness of the system, whereas offline detection could be used by a system designer to identify potential flaws in the dialogue design. In experimental evaluations on system logs from three different dialogue systems that vary in their dialogue strategy, the proposed models performed substantially better than the majority class baseline models.

Place, publisher, year, edition, pages
2015. 354-363 p.
National Category
Computer Science Language Technology (Computational Linguistics)
Identifiers
URN: urn:nbn:se:kth:diva-180406OAI: oai:DiVA.org:kth-180406DiVA: diva2:893730
Conference
16th Annual Meeting of the Special Interest Group on Discourse and Dialogue (SIGDIAL)
Note

QC 20160120

Available from: 2016-01-13 Created: 2016-01-13 Last updated: 2016-01-20Bibliographically approved

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Meena, RaveeshDavid Lopes, JoséSkantze, GabrielGustafson, Joakim
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ReferencesLink to record
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