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
- 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)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-4/W17-5547.pdf