A data-driven model of explanations for a chatbot that helps to practice conversation in a foreign language

Sviatlana Höhn


Abstract
This article describes a model of other-initiated self-repair for a chatbot that helps to practice conversation in a foreign language. The model was developed using a corpus of instant messaging conversations between German native and non-native speakers. Conversation Analysis helped to create computational models from a small number of examples. The model has been validated in an AIML-based chatbot. Unlike typical retrieval-based dialogue systems, the explanations are generated at run-time from a linguistic database.
Anthology ID:
W17-5547
Volume:
Proceedings of the 18th Annual SIGdial Meeting on Discourse and Dialogue
Month:
August
Year:
2017
Address:
Saarbrücken, Germany
Editors:
Kristiina Jokinen, Manfred Stede, David DeVault, Annie Louis
Venue:
SIGDIAL
SIG:
SIGDIAL
Publisher:
Association for Computational Linguistics
Note:
Pages:
395–405
Language:
URL:
https://aclanthology.org/W17-5547
DOI:
10.18653/v1/W17-5547
Bibkey:
Cite (ACL):
Sviatlana Höhn. 2017. A data-driven model of explanations for a chatbot that helps to practice conversation in a foreign language. In Proceedings of the 18th Annual SIGdial Meeting on Discourse and Dialogue, pages 395–405, Saarbrücken, Germany. Association for Computational Linguistics.
Cite (Informal):
A data-driven model of explanations for a chatbot that helps to practice conversation in a foreign language (Höhn, SIGDIAL 2017)
Copy Citation:
PDF:
https://aclanthology.org/W17-5547.pdf