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
Venues:
INLG | WS
SIG:
SIGGEN
Publisher:
Association for Computational Linguistics
Note:
Pages:
1–7
Language:
URL:
https://aclanthology.org/W18-6901
DOI:
10.18653/v1/W18-6901
Bibkey:
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., 2018)
Copy Citation:
PDF:
https://aclanthology.org/W18-6901.pdf