Context-sensitive Natural Language Generation for robot-assisted second language tutoring
Bram Willemsen, Jan de Wit, Emiel Krahmer, Mirjam de Haas, Paul Vogt
Abstract
This paper describes the L2TOR intelligent tutoring system (ITS), focusing primarily on its output generation module. The L2TOR ITS is developed for the purpose of investigating the efficacy of robot-assisted second language tutoring in early childhood. We explain the process of generating contextually-relevant utterances, such as task-specific feedback messages, and discuss challenges regarding multimodality and multilingualism for situated natural language generation from a robot tutoring perspective.- Anthology ID:
- W18-6901
- Volume:
- Proceedings of the Workshop on NLG for Human–Robot Interaction
- Month:
- November
- Year:
- 2018
- Address:
- Tilburg, The Netherlands
- Editors:
- Mary Ellen Foster, Hendrik Buschmeier, Dimitra Gkatzia
- Venue:
- INLG
- SIG:
- SIGGEN
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 1–7
- Language:
- URL:
- https://aclanthology.org/W18-6901
- DOI:
- 10.18653/v1/W18-6901
- Cite (ACL):
- Bram Willemsen, Jan de Wit, Emiel Krahmer, Mirjam de Haas, and Paul Vogt. 2018. Context-sensitive Natural Language Generation for robot-assisted second language tutoring. In Proceedings of the Workshop on NLG for Human–Robot Interaction, pages 1–7, Tilburg, The Netherlands. Association for Computational Linguistics.
- Cite (Informal):
- Context-sensitive Natural Language Generation for robot-assisted second language tutoring (Willemsen et al., INLG 2018)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-4/W18-6901.pdf