Embodied agents for multi-party dialogue in immersive virtual worlds
Proceedings of the first international joint conference on Autonomous agents and multiagent systems: part 2
A Computational Theory of Grounding in Natural Language Conversation
A Computational Theory of Grounding in Natural Language Conversation
Learning Smooth, Human-Like Turntaking in Realtime Dialogue
IVA '08 Proceedings of the 8th international conference on Intelligent Virtual Agents
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
Optimizing endpointing thresholds using dialogue features in a spoken dialogue system
SIGdial '08 Proceedings of the 9th SIGdial Workshop on Discourse and Dialogue
Importance-Driven Turn-Bidding for spoken dialogue systems
ACL '10 Proceedings of the 48th Annual Meeting 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
Multiparty turn taking in situated dialog: study, lessons, and directions
SIGDIAL '11 Proceedings of the SIGDIAL 2011 Conference
Learning speaker, addressee and overlap detection models from multimodal streams
Proceedings of the 14th ACM international conference on Multimodal interaction
Managing chaos: models of turn-taking in character-multichild interactions
Proceedings of the 15th ACM on International conference on multimodal interaction
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We present a decision-theoretic approach for guiding turn taking in a spoken dialog system operating in multiparty settings. The proposed methodology couples inferences about multiparty conversational dynamics with assessed costs of different outcomes, to guide turn-taking decisions. Beyond considering uncertainties about outcomes arising from evidential reasoning about the state of a conversation, we endow the system with awareness and methods for handling uncertainties stemming from computational delays in its own perception and production. We illustrate via sample cases how the proposed approach makes decisions, and we investigate the behaviors of the proposed methods via a retrospective analysis on logs collected in a multiparty interaction study.