The DOI matches its Crossref record; 18 of the 18 references it cites were found in a registry or an index.
Contextual recognition of head gestures,
Abstract
Head pose and gesture offer several key conversational grounding cues and are used extensively in face-to-face interaction among people. We investigate how dialog context from an embodied conversational agent (ECA) can improve visual recognition of user gestures. We present a recognition framework which (1) extracts contextual features from an ECA's dialog manager, (2) computes a prediction of head nod and head shakes, and (3) integrates the contextual predictions with the visual observation of a vision-based head gesture recognizer. We found a subset of lexical, punctuation and timing features that are easily available in most ECA architectures and can be used to learn how to predict user feedback. Using a discriminative approach to contextual prediction and multi-modal integration, we were able to improve the performance of head gesture detection even when the topic of the test set was significantly different than the training set.
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“In their study, they found that classification of nods and shakes was possible to do with high accuracy when the visual data from a camera sensor was combined with a prediction from dialogue context.”
From Modeling Feedback in Interaction With Conversational Agents—A Review (2022) · cites this paper as Morency et al., 2005
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- 10.5555/874061.875409 · DOI
- 10.5555/946247.946665 · DOI
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Metadata
- Authors
- Morency, L.-P., Sidner, C., Lee, C., & Darrell, T.
- Affiliations
- Massachusetts Institute of Technology (US)
- Mitsubishi Electric Research Laboratories (United States) (US)
- Venue
- Proceedings of the 7th international conference on Multimodal interfaces
- Publisher
- ACM
- Published
- 2005-10-04
- Pages
- 18-24
- OpenAlex
- W2112618815
- Cited by
- 130
- References
- 18
- Citations by year
- 2026: 2 · 2024: 2 · 2023: 3 · 2022: 4 · 2021: 2 · 2020: 4 · 2019: 1 · 2018: 3 · 2017: 5 · 2016: 4 · 2015: 5 · 2014: 4 · 2013: 12 · 2012: 7
- FWCI
- 7.61
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- INTERNATIONAL CONFERENCE ON MULTIMODAL INTERACTION (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Speech and dialogue systems
- Physical Sciences › Computer Science › Human-Computer Interaction › Hand Gesture Recognition Systems
- Physical Sciences › Computer Science › Artificial Intelligence › Emotion and Mood Recognition
- Keywords
- head gesture recognition, head orientation, head nodding, head shake, embodied conversational agents, contextual features, multimodal integration, lexical features, timing features, conversational grounding
About these checks
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.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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