Designing and Evaluating an Adaptive Spoken Dialogue System
User Modeling and User-Adapted Interaction
The Architecture of Why2-Atlas: A Coach for Qualitative Physics Essay Writing
ITS '02 Proceedings of the 6th International Conference on Intelligent Tutoring Systems
ITS '02 Proceedings of the 6th International Conference on Intelligent Tutoring Systems
Predicting user reactions to system error
ACL '01 Proceedings of the 39th Annual Meeting on Association for Computational Linguistics
Learning trees and rules with set-valued features
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 1
Social robots as mediators between users and smart environments
Proceedings of the 12th international conference on Intelligent user interfaces
User modeling and adaptation in health promotion dialogs with an animated character
Journal of Biomedical Informatics - Special issue: Dialog systems for health communications
`O Francesca, ma che sei grulla?' Emotions and Irony in Persuasion Dialogues
AI*IA '07 Proceedings of the 10th Congress of the Italian Association for Artificial Intelligence on AI*IA 2007: Artificial Intelligence and Human-Oriented Computing
'You are Sooo Cool, Valentina!' Recognizing Social Attitude in Speech-Based Dialogues with an ECA
ACII '07 Proceedings of the 2nd international conference on Affective Computing and Intelligent Interaction
Image and Vision Computing
Dynamic user modeling in health promotion dialogs
ACII'05 Proceedings of the First international conference on Affective Computing and Intelligent Interaction
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Human tutors detect and respond to student emotional states, but current machine tutors do not. Our preliminary machine learning experiments involving transcription, emotion annotation and automatic feature extraction from our human-human spoken tutoring corpus indicate that the spoken tutoring system we are developing can be enhanced to automatically predict and adapt to student emotional states.