Affective computing
Modeling Multimodal Expression of User's Affective Subjective Experience
User Modeling and User-Adapted Interaction
2005 Special Issue: Challenges in real-life emotion annotation and machine learning based detection
Neural Networks - Special issue: Emotion and brain
A User Model of Psycho-physiological Measure of Emotion
UM '07 Proceedings of the 11th international conference on User Modeling
Annotation of Emotion in Dialogue: The Emotion in Cooperation Project
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
Inter-coder agreement for computational linguistics
Computational Linguistics
When Human Coders (and Machines) Disagree on the Meaning of Facial Affect in Spontaneous Videos
IVA '09 Proceedings of the 9th International Conference on Intelligent Virtual Agents
Standoff coordination for multi-tool annotation in a dialogue corpus
LAW '07 Proceedings of the Linguistic Annotation Workshop
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The Rovereto Emotion and Cooperation Corpus (RECC) is a new resource collected to investigate the relationship between cooperation and emotions in an interactive setting. Previous attempts at collecting corpora to study emotions have shown that this data are often quite difficult to classify and analyse, and coding schemes to analyse emotions are often found not to be reliable. We collected a corpus of task-oriented (MapTask-style) dialogues in Italian, in which the segments of emotional interest are identified using psycho-physiological indexes (Heart Rate and Galvanic Skin Conductance) which are highly reliable. We then annotated these segments in accordance with novel multimodal annotation schemes for cooperation (in terms of effort) and facial expressions (an indicator of emotional state). High agreement was obtained among coders on all the features. The RECC corpus is to our knowledge the first resource with psycho-physiological data aligned with verbal and nonverbal behaviour data.