Timing and entrainment of multimodal backchanneling behavior for an embodied conversational agent
Abstract
We report on an analysis of feedback behavior in an Active Listening Corpus as produced verbally, visually (head movement) and bimodally. The behavior is modeled in an embodied conversational agent and displayed in a conversation with a real human to human participants for perceptual evaluation. Five strategies for the timing of backchannels are compared: copying the timing of the original human listener, producing backchannels at randomly selected times, producing backchannels according to high level timing distributions relative to the interlocutor's utterance and pauses, or according to local entrainment to the interlocutors' vowels, or according to both. Human observers judge that models with global timing distributions miss less opportunities for backchanneling than random timing.
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Forty percent of the listener's head gestures overlapped with the end of the speaker's turn, which indicates that they serve as a turn-yielding cue.
“Forty percent of the listener's head gestures overlapped with the end of the speaker's turn, which indicates that they serve as a turn-yielding cue.”
From Modeling Feedback in Interaction With Conversational Agents—A Review (2022) · cites this paper as Inden et al., 2013
Head gestures from the listener were increasingly more likely as time passes in the speaker's turn.
“Inden et al. (2013) found that head gestures from the listener were increasingly more likely as time passes in the speaker's turn.”
From Modeling Feedback in Interaction With Conversational Agents—A Review (2022) · cites this paper as Inden et al., 2013
Cites
Modeling embodied feedback with virtual humans,
Kopp, S., Allwood, J., Grammer, K., Ahlsen, E., & Stocksmeier, T. (2008) · Lecture Notes in Computer Science · doi:10.1007/978-3-540-79037-2_2 · Cited by 71 · see citing works
A multimodal analysis of vocal and visual backchannels in spontaneous dialogs,
Truong, K. P., Poppe, R., Kok, I. D., & Heylen, D. (2011) · Interspeech 2011 · doi:10.21437/interspeech.2011-744 · Cited by 33 · see citing works
Fluid Semantic Back-Channel Feedback in Dialogue: Challenges and Progress
Jonsdottir, G. R., Gratch, J., Fast, E., & Thórisson, K. R. (2007) · Lecture Notes in Computer Science · doi:10.1007/978-3-540-74997-4_15 · Cited by 29 · see citing works
Listener head gestures and verbal feedback expressions in a distraction task
Włodarczak, M., Buschmeier, H., Malisz, Z., Kopp, S., & Wagner, P. (2012) · Zenodo · doi:10.5281/zenodo.3234894 · Cited by 17 · see citing works
Self-citationPerceptual evaluation of backchannel strategies for artificial listeners
Poppe, R., Truong, K. P., & Heylen, D. (2013) · Autonomous Agents and Multi-Agent Systems · doi:10.1007/s10458-013-9219-z · Cited by 14 · see citing works
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Modeling Feedback in Interaction With Conversational Agents—A Review
Axelsson, A., Buschmeier, H., & Skantze, G. (2022) · Frontiers in Computer Science · doi:10.3389/fcomp.2022.744574 · Cited by 33 · see citing works
The ALICO corpus: analysing the active listener
Malisz, Z., Włodarczak, M., Buschmeier, H., Skubisz, J., Kopp, S., & Wagner, P. (2016) · Language Resources and Evaluation · doi:10.1007/s10579-016-9355-6 · Cited by 23 · see citing works
Self-citation
- Authors
- Inden, B., Malisz, Z., Wagner, P., & Wachsmuth, I.
- Affiliations
- Bielefeld University (DE)
- Venue
- Proceedings of the 15th ACM on International conference on multimodal interaction
- Publisher
- ACM
- Published
- 2013-12-09
- Pages
- 181-188
- OpenAlex
- W2063643001
- Cited by
- 25
- References
- 5
- Citations by year
- 2026: 1 · 2025: 2 · 2024: 2 · 2023: 3 · 2022: 2 · 2020: 1 · 2019: 3 · 2018: 3 · 2017: 1 · 2016: 2 · 2015: 2 · 2014: 3
- FWCI
- 1.51
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- INTERNATIONAL CONFERENCE ON MULTIMODAL INTERACTION (publishedVersion)
- PUB – Publications at Bielefeld University (Bielefeld University) (submittedVersion)
- Funders
- Deutsche Forschungsgemeinschaft
- 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
- backchanneling, embodied conversational agents, multimodal feedback, head movement, human-agent interaction
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