The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
A Storytelling Robot: Modeling and Evaluation of Human-like Gaze Behavior
Abstract
Engaging storytelling is a necessary skill for humanoid robots if they are to be used in education and entertainment applications. Storytelling requires that the humanoid robot be aware of its audience and able to direct its gaze in a natural way. In this paper, we explore how human gaze can be modeled and implemented on a humanoid robot to create a natural, human-like behavior for storytelling. Our gaze model integrates data collected from a human storyteller and a discourse structure model developed by Cassell and her colleagues for human-like conversational agents (1994). We used this model to direct the gaze of a humanoid robot, Honda's ASIMO, as he recited a Japanese fairy tale using a pre-recorded human voice. We assessed the efficacy of this gaze algorithm by manipulating the frequency of ASIMO's gaze between two participants and used pre and post questionnaires to assess whether participants evaluated the robot more positively and did better on a recall task when ASIMO looked at them more. We found that participants performed significantly better in recalling ASIMO's story when the robot looked at them more. Our results also showed significant differences in how men and women evaluated ASIMO based on the frequency of gaze they received from the robot. Our study adds to the growing evidence that there are many commonalities between human-human communication and human-robot communication
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Cites
Gaze and eye contact: a research review
Kleinke, C. L. (1986) · Psychological Bulletin · doi:10.1037/0033-2909.100.1.78 · Cited by 1,455
Inference of attitudes from the posture, orientation, and distance of a communicator.
Mehrabian, A. (1968) · Journal of Consulting and Clinical Psychology · doi:10.1037/h0025906 · Cited by 259
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Kim, K., Boelling, L., Haesler, S., Bailenson, J., Bruder, G., & Welch, G. F. (2018) · 2018 IEEE International Symposium on Mixed and Augmented Reality (ISMAR) · doi:10.1109/ismar.2018.00039 · Cited by 206
Robots in Groups and Teams: A Literature Review
Sebo, S., Stoll, B., Scassellati, B., & Jung, M. F. (2020) · Proceedings of the ACM on Human-Computer Interaction · doi:10.1145/3415247 · Cited by 158
Towards human-like spoken dialogue systems
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Learning-based modeling of multimodal behaviors for humanlike robots
Huang, C.-M., & Mutlu, B. (2014) · Proceedings of the 2014 ACM/IEEE international conference on Human-robot interaction · doi:10.1145/2559636.2559668 · Cited by 99
Self-citationPitsch, K., Kuzuoka, H., Suzuki, Y., Sussenbach, L., Luff, P., & Heath, C. (2009) · RO-MAN 2009 - The 18th IEEE International Symposium on Robot and Human Interactive Communication · doi:10.1109/roman.2009.5326167 · Cited by 64
Gaze and Attention Management for Embodied Conversational Agents
Pejsa, T., Andrist, S., Gleicher, M., & Mutlu, B. (2015) · ACM Transactions on Interactive Intelligent Systems · doi:10.1145/2724731 · Cited by 61
Self-citationMy Bad! Repairing Intelligent Voice Assistant Errors Improves Interaction
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Self-citationHRLB⌃2: A Reinforcement Learning Based Framework for Believable Bots
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Look at Me When I Talk to You: A Video Dataset to Enable Voice Assistants to Recognize Errors
Cuadra, A., Lee, H., Cho, J., & Ju, W. (2021) · arXiv · doi:10.48550/arxiv.2104.07153 · Cited by 5
Metadata
- Authors
- Mutlu, B., Forlizzi, J., & Hodgins, J.
- Venue
- 2006 6th IEEE-RAS International Conference on Humanoid Robots
- Publisher
- IEEE
- Published
- 2006-12
- Pages
- 518-523
- OpenAlex
- W2543757304
- Cited by
- 348
- References
- 2
- FWCI
- 7.68
- Type
- conference paper
- Language
- en
- Open access
- closed
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