Integrated learning for interactive synthetic characters
Proceedings of the 29th annual conference on Computer graphics and interactive techniques
Effects of anticipatory action on human-robot teamwork efficiency, fluency, and perception of team
Proceedings of the ACM/IEEE international conference on Human-robot interaction
Footing in human-robot conversations: how robots might shape participant roles using gaze cues
Proceedings of the 4th ACM/IEEE international conference on Human robot interaction
A finite-state turn-taking model for spoken dialog systems
NAACL '09 Proceedings of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics
Facilitating multiparty dialog with gaze, gesture, and speech
International Conference on Multimodal Interfaces and the Workshop on Machine Learning for Multimodal Interaction
Designing Interactions for Robot Active Learners
IEEE Transactions on Autonomous Mental Development
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In human cooperation, the concurrent usage of multiple social modalities such as speech, gesture, and gaze results in robust and efficient communicative acts. Such multimodality in combination with reciprocal intentions supports fluent turn-taking. I hypothesize that human-robot turn-taking can be made more fluent through appropriate timing of multimodal actions. Managing timing includes understanding the impact that timing can have on interactions as well as having a control system that supports the manipulation of such timing. To this end, I propose to develop a computational turn-taking model of the timing and information flow of reciprocal interactions. I also propose to develop an architecture based on the timed Petri net (TPN) for the generation of coordinated multimodal behavior, inside of which the turn-taking model will regulate turn timing and action initiation and interruption in order to seize and yield control. Through user studies in multiple domains, I intend to demonstrate the system's generality and evaluate the system on balance of control, fluency, and task effectiveness.