Introduction to Multiagent Systems
Introduction to Multiagent Systems
Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data
ICML '01 Proceedings of the Eighteenth International Conference on Machine Learning
A Reactive-Deliberative Model of Dialogue Agency
ECAI '96 Proceedings of the Workshop on Intelligent Agents III, Agent Theories, Architectures, and Languages
Can we hear the prosody of smile?
Speech Communication - Special issue on speech and emotion
A shallow model of backchannel continuers in spoken dialogue
EACL '03 Proceedings of the tenth conference on European chapter of the Association for Computational Linguistics - Volume 1
Natural behavior of a listening agent
Lecture Notes in Computer Science
A probabilistic multimodal approach for predicting listener backchannels
Autonomous Agents and Multi-Agent Systems
The multiLis corpus - dealing with individual differences in nonverbal listening behavior
Proceedings of the Third COST 2102 international training school conference on Toward autonomous, adaptive, and context-aware multimodal interfaces: theoretical and practical issues
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In this paper we will look into reactive models for embodied conversational agents for generating smiling behavior. One trigger for smiling behaviour is smiling of the human interlocutor which is used in reactive models based on mimicry. However, other features might be useful as well. In order to develop such models we look at the nonverbal context of smiles in human-human conversation. We make a distinction between three types of smiles - amused, polite and embarrassed - and highlighted differences in context where each type occurs in conversation. Using machine learning techniques we have build predictive models using the nonverbal contextual features analyzed. Results show that reactive models can offer an interesting contribution to the generation of smiling behaviors.