The dialogue breakdown detection challenge: Task description, datasets, and evaluation metrics

Ryuichiro Higashinaka, Kotaro Funakoshi, Yuka Kobayashi, Michimasa Inaba


Abstract
Dialogue breakdown detection is a promising technique in dialogue systems. To promote the research and development of such a technique, we organized a dialogue breakdown detection challenge where the task is to detect a system’s inappropriate utterances that lead to dialogue breakdowns in chat. This paper describes the design, datasets, and evaluation metrics for the challenge as well as the methods and results of the submitted runs of the participants.
Anthology ID:
L16-1502
Volume:
Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16)
Month:
May
Year:
2016
Address:
Portorož, Slovenia
Editors:
Nicoletta Calzolari, Khalid Choukri, Thierry Declerck, Sara Goggi, Marko Grobelnik, Bente Maegaard, Joseph Mariani, Helene Mazo, Asuncion Moreno, Jan Odijk, Stelios Piperidis
Venue:
LREC
SIG:
Publisher:
European Language Resources Association (ELRA)
Note:
Pages:
3146–3150
Language:
URL:
https://aclanthology.org/L16-1502
DOI:
Bibkey:
Cite (ACL):
Ryuichiro Higashinaka, Kotaro Funakoshi, Yuka Kobayashi, and Michimasa Inaba. 2016. The dialogue breakdown detection challenge: Task description, datasets, and evaluation metrics. In Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16), pages 3146–3150, Portorož, Slovenia. European Language Resources Association (ELRA).
Cite (Informal):
The dialogue breakdown detection challenge: Task description, datasets, and evaluation metrics (Higashinaka et al., LREC 2016)
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PDF:
https://preview.aclanthology.org/nschneid-patch-1/L16-1502.pdf