Gaze and Attention Management for Embodied Conversational Agents
Abstract
To facilitate natural interactions between humans and embodied conversational agents (ECAs), we need to endow the latter with the same nonverbal cues that humans use to communicate. Gaze cues in particular are integral in mechanisms for communication and management of attention in social interactions, which can trigger important social and cognitive processes, such as establishment of affiliation between people or learning new information. The fundamental building blocks of gaze behaviors are gaze shifts : coordinated movements of the eyes, head, and body toward objects and information in the environment. In this article, we present a novel computational model for gaze shift synthesis for ECAs that supports parametric control over coordinated eye, head, and upper body movements. We employed the model in three studies with human participants. In the first study, we validated the model by showing that participants are able to interpret the agent’s gaze direction accurately. In the second and third studies, we showed that by adjusting the participation of the head and upper body in gaze shifts, we can control the strength of the attention signals conveyed, thereby strengthening or weakening their social and cognitive effects. The second study shows that manipulation of eye--head coordination in gaze enables an agent to convey more information or establish stronger affiliation with participants in a teaching task, while the third study demonstrates how manipulation of upper body…
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The best compromise for an ECA's gaze is to fully look towards the user when speaking (affiliative strategy) and fully look towards the object of interest when making mentions of it (referential strategy).
“the best compromise is for the ECA to fully look towards the user when speaking (affiliative strategy) and fully looking towards the object of interest when making mentions of it (referential strategy).”
From Usability assessment of interaction management support in LOUISE, an ECA-based user interface for elders with cognitive impairment (2018) · cites this paper as [45]
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Cuadra, A., Li, S., Lee, H., Cho, J., & Ju, W. (2021) · Proceedings of the ACM on Human-Computer Interaction · doi:10.1145/3449101 · Cited by 52 · see citing works
Wargnier, P., Benveniste, S., Jouvelot, P., & Rigaud, A.-S. (2018) · Technology and Disability · doi:10.3233/tad-180189 · Cited by 32 · see citing works
- Authors
- Pejsa, T., Andrist, S., Gleicher, M., & Mutlu, B.
- Affiliations
- University of Wisconsin-Madison, Department of Computer Sciences, W. Dayton St., Madison, WI
- University of Wisconsin–Madison (US)
- Venue
- ACM Transactions on Interactive Intelligent Systems
- Published
- 2015-03-25
- Volume
- 5
- Issue
- 1
- Pages
- 1-34
- ISSN
- 2160-6455 (ISSN-L)
- 2160-6463
- OpenAlex
- W2012804445
- Cited by
- 61
- References
- 0
- Citations by year
- 2026: 1 · 2025: 5 · 2024: 5 · 2023: 6 · 2022: 9 · 2021: 6 · 2020: 7 · 2019: 5 · 2018: 4 · 2017: 6 · 2016: 5 · 2015: 1 · 2014: 1
- FWCI
- 8.74
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- ACM Transactions on Interactive Intelligent Systems (publishedVersion)
- Funders
- National Science Foundation (1017952)
- Topics
- Social Sciences › Psychology › Social Psychology › Social Robot Interaction and HRI
- Physical Sciences › Computer Science › Human-Computer Interaction › Gaze Tracking and Assistive Technology
- Physical Sciences › Computer Science › Artificial Intelligence › Speech and dialogue systems
- Keywords
- embodied conversational agents, gaze shifts, gaze cues, nonverbal communication, attention management, eye-head coordination, gaze direction perception, affiliation, teaching, social interaction
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