Models for multiparty engagement in open-world dialog
Open accessAbstract
We present computational models that allow spoken dialog systems to handle multi-participant engagement in open, dynamic environments, where multiple people may enter and leave conversations, and interact with the system and with others in a natural manner. The models for managing the engagement process include components for (1) sensing the engagement state, actions and intentions of multiple agents in the scene, (2) making engagement decisions (i.e. whom to engage with, and when) and (3) rendering these decisions in a set of coordinated low-level behaviors in an embodied conversational agent. We review results from a study of interactions "in the wild" with a system that implements such a model.
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The user's body pose can be used to estimate their intent to engage with an embodied agent.
“The user's body pose can be used to estimate their intent to engage with an embodied agent (Bohus and Horvitz, 2009; Sanghvi et al., 2011; Schwarz et al., 2014).”
From Modeling Feedback in Interaction With Conversational Agents—A Review (2022) · cites this paper as Bohus and Horvitz, 2009
Bohus and Horvitz found that by using a subset of these features, systems could learn to predict the moment of engagement or disengagement by as much as 4 seconds, implying that the body pose features that humans use to display an intent to engage or disengage happen over a surprisingly long span.
“Bohus and Horvitz found that by using a subset of these features, systems could learn to predict the moment of engagement or disengagement by as much as 4 seconds, implying that the body pose features that humans use to display an intent to engage or disengage happen over a surprisingly long span.”
From Modeling Feedback in Interaction With Conversational Agents—A Review (2022) · cites this paper as Bohus and Horvitz, 2009
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Look versus leap: computing value of information with high-dimensional streaming evidence
Rosenthal, S. L., Bohus, D., Kamar, E. S., & Horvitz, E. (2013) · Cited by 5 · see citing works
Self-citation
- Authors
- Bohus, D., & Horvitz, E.
- Affiliations
- Microsoft (United States) (US)
- Venue
- Proceedings of the SIGDIAL 2009 Conference on The 10th Annual Meeting of the Special Interest Group on Discourse and Dialogue - SIGDIAL '09
- Published
- 2009
- Pages
- 225-234
- OpenAlex
- W2044924490
- Cited by
- 145
- References
- 10
- Citations by year
- 2026: 6 · 2025: 4 · 2024: 7 · 2023: 4 · 2022: 5 · 2021: 4 · 2020: 8 · 2019: 12 · 2018: 9 · 2017: 8 · 2016: 13 · 2015: 12 · 2014: 12 · 2013: 12 · 2012: 9
- FWCI
- 6.80
- Type
- conference paper
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Annual Meeting of the Special Interest Group on Discourse and Dialogue (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Speech and dialogue systems
- Social Sciences › Psychology › Social Psychology › Social Robot Interaction and HRI
- Social Sciences › Arts and Humanities › Language and Linguistics › Language, Discourse, Communication Strategies
- Keywords
- spoken dialogue systems, embodied conversational agents, multi-agent interaction, dynamic environments
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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