Abstract
In this paper, we describe our setting and the architecture of our LLM-based dialogue system embodied in a social robot and able to have multi-party conversations. Each component is detailed, and a video of the full system is available with the appropriate components highlighted in real-time. Our system decides when it should take its turn, generates human-like clarification requests when the patient pauses mid-utterance, answers in-domain questions (grounding to the in-prompt knowledge), and responds appropriately to out-of-domain requests (like generating jokes or quizzes).
| Original language | English |
|---|---|
| Title of host publication | HRI '24: Companion of the 2024 ACM/IEEE International Conference on Human-Robot Interaction |
| Publisher | Association for Computing Machinery |
| Pages | 1273-1275 |
| Number of pages | 3 |
| ISBN (Print) | 9798400703232 |
| DOIs | |
| Publication status | Published - 11 Mar 2024 |
| Event | 19th Annual ACM/IEEE International Conference on Human-Robot Interaction 2024 - Boulder, United States Duration: 11 Mar 2024 → 15 Mar 2024 |
Conference
| Conference | 19th Annual ACM/IEEE International Conference on Human-Robot Interaction 2024 |
|---|---|
| Abbreviated title | HRI 2024 |
| Country/Territory | United States |
| City | Boulder |
| Period | 11/03/24 → 15/03/24 |
Keywords
- accessibility
- conversational AI
- human-robot interaction
- large language models
- multi-party dialogue
- social robots
ASJC Scopus subject areas
- Artificial Intelligence
- Human-Computer Interaction
- Electrical and Electronic Engineering