The Wisdom of Crowds
Logarithmic opinion pools for conditional random fields
ACL '05 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics
Head gestures for perceptual interfaces: The role of context in improving recognition
Artificial Intelligence
A probabilistic multimodal approach for predicting listener backchannels
Autonomous Agents and Multi-Agent Systems
Parasocial consensus sampling: combining multiple perspectives to learn virtual human behavior
Proceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems: volume 1 - Volume 1
Latent mixture of discriminative experts for multimodal prediction modeling
COLING '10 Proceedings of the 23rd International Conference on Computational Linguistics
Modeling wisdom of crowds using latent mixture of discriminative experts
HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies: short papers - Volume 2
Joint ACM workshop on human gesture and behavior understanding: (J-HGBU'11)
MM '11 Proceedings of the 19th ACM international conference on Multimedia
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Face-to-face communication is a highly dynamic process where participants mutually exchange and interpret linguistic and gestural signals. Even when only one person speaks at the time, other participants exchange information continuously amongst themselves and with the speaker through gesture, gaze, posture and facial expressions. To correctly interpret the high-level communicative signals, an observer needs to jointly integrate all spoken words, subtle prosodic changes and simultaneous gestures from all participants. In this paper, we present our ongoing research effort at USC MultiComp Lab to create models of human communication dynamic that explicitly take into consideration the multimodal and interpersonal aspects of human face-to-face interactions. The computational framework presented in this paper has wide applicability, including the recognition of human social behaviors, the synthesis of natural animations for robots and virtual humans, improved multimedia content analysis, and the diagnosis of social and behavioral disorders (e.g., autism spectrum disorder).