Abstract
Speech overlap is a common phenomenon in natural conversation and in task-oriented interactions. As human-robot interaction (HRI) becomes more sophisticated, the need to effectively manage turn-taking and resolve overlap becomes more important. In this paper, we introduce a computational model for speech overlap resolution in embodied artificial agents. The model identifies when overlap has occurred and uses timing information, dialogue history, and the agent’s goals to generate context-appropriate behavior. We implement this model in a Nao robot using the DIARC cognitive robotic architecture. The model is evaluated on a corpus of task-oriented human dialogue, and we find that the robot can replicate many of the most common overlap resolution behaviors found in the human data.- Anthology ID:
- W18-5011
- Volume:
- Proceedings of the 19th Annual SIGdial Meeting on Discourse and Dialogue
- Month:
- July
- Year:
- 2018
- Address:
- Melbourne, Australia
- Editors:
- Kazunori Komatani, Diane Litman, Kai Yu, Alex Papangelis, Lawrence Cavedon, Mikio Nakano
- Venue:
- SIGDIAL
- SIG:
- SIGDIAL
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 99–109
- Language:
- URL:
- https://aclanthology.org/W18-5011
- DOI:
- 10.18653/v1/W18-5011
- Cite (ACL):
- Felix Gervits and Matthias Scheutz. 2018. Pardon the Interruption: Managing Turn-Taking through Overlap Resolution in Embodied Artificial Agents. In Proceedings of the 19th Annual SIGdial Meeting on Discourse and Dialogue, pages 99–109, Melbourne, Australia. Association for Computational Linguistics.
- Cite (Informal):
- Pardon the Interruption: Managing Turn-Taking through Overlap Resolution in Embodied Artificial Agents (Gervits & Scheutz, SIGDIAL 2018)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-4/W18-5011.pdf