Shaping a social robot’s humor with Natural Language Generation and socially-aware reinforcement learning

Hannes Ritschel, Elisabeth André


Abstract
Humor is an important aspect in human interaction to regulate conversations, increase interpersonal attraction and trust. For social robots, humor is one aspect to make interactions more natural, enjoyable, and to increase credibility and acceptance. In combination with appropriate non-verbal behavior, natural language generation offers the ability to create content on-the-fly. This work outlines the building-blocks for providing an individual, multimodal interaction experience by shaping the robot’s humor with the help of Natural Language Generation and Reinforcement Learning based on human social signals.
Anthology ID:
W18-6903
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:
12–16
Language:
URL:
https://aclanthology.org/W18-6903
DOI:
10.18653/v1/W18-6903
Bibkey:
Cite (ACL):
Hannes Ritschel and Elisabeth André. 2018. Shaping a social robot’s humor with Natural Language Generation and socially-aware reinforcement learning. In Proceedings of the Workshop on NLG for Human–Robot Interaction, pages 12–16, Tilburg, The Netherlands. Association for Computational Linguistics.
Cite (Informal):
Shaping a social robot’s humor with Natural Language Generation and socially-aware reinforcement learning (Ritschel & André, 2018)
Copy Citation:
PDF:
https://aclanthology.org/W18-6903.pdf