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Cited by 271

The DOI matches its Crossref record; 23 of the 23 references it cites were found in a registry or an index.

The impact of eye gaze on communication using humanoid avatars

Garau, Maia, Slater, Mel, Bee, Simon, Sasse, Martina Angela·2001·Proceedings of the SIGCHI Conference on Human Factors in Computing Systems

Abstract

In this paper we describe an experiment designed to investigate the importance of eye gaze in humanoid avatar's representing people engaged in conversation. We compare responses to dyadic conversations in four mediated conditions: video, audio-only, and two avatar conditions. The avatar conditions differed only in their treatment of eye gaze. In the random-gaze condition the avatars head and eye animations were unrelated to conversational flow. In the informed-gaze condition, they were related to turn-taking during the conversation. The head animations were tracked and the eye animations were inferred from the audio stream. Our comparative analysis of 100 post-experiment questionnaires showed that the random-gaze avatar did not improve on audio-only communication. The informed-gaze avatar significantly outperformed the random-gaze model and also outperformed audio-only on several response measures. We conclude that an avatar whose gaze behaviour is related to the conversation provides a marked improvement on an avatar that merely exhibits liveliness.

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Metadata

Authors
Garau, M., Slater, M., Bee, S., & Sasse, M. A.
Venue
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Publisher
ACM
Published
2001-03
Pages
309-316
OpenAlex
W1988023718
Cited by
271
References
23
FWCI
50.04
Type
conference paper
Language
en
Open access
closed

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CoChat. (2026). Citation check: The impact of eye gaze on communication using humanoid avatars. https://app.cochat.ai/papers/10.1145/365024.365121
The paper
Garau, M., Slater, M., Bee, S., & Sasse, M. A. (2001). The impact of eye gaze on communication using humanoid avatars. Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. https://doi.org/10.1145/365024.365121

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.