The measurement of end-user computing satisfaction
MIS Quarterly
Data Mining: Practical Machine Learning Tools and Techniques, Second Edition (Morgan Kaufmann Series in Data Management Systems)
Automatic detection of learner's affect from conversational cues
User Modeling and User-Adapted Interaction
On the Use of Kappa Coefficients to Measure the Reliability of the Annotation of Non-acted Emotions
PIT '08 Proceedings of the 4th IEEE tutorial and research workshop on Perception and Interactive Technologies for Speech-Based Systems: Perception in Multimodal Dialogue Systems
DEXA '10 Proceedings of the 2010 Workshops on Database and Expert Systems Applications
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We describe the work on infusion of emotion into limited-task autonomous spoken conversational agents (SCAs) situated in the domestic environment, using a N eed-inspired task-independent Emo tion model (NEMO). In order to demonstrate the generation of affect through the use of the model, we describe the work of integrating it with a natural-language mixed-initiative HiFi-control SCA. NEMO and the host system communicates externally, removing the need for the Dialog Manager to be modified as done in most existing dialog systems, in order to be adaptive. We also summarize the work on automatic affect prediction, namely frustration and contentment from dialog features, a non-conventional source, in the attempt of moving towards a more user-centric approach.