Toward Machine Emotional Intelligence: Analysis of Affective Physiological State
IEEE Transactions on Pattern Analysis and Machine Intelligence - Graph Algorithms and Computer Vision
A control model of the movement of attention
Neural Networks
Speech Communication - Special issue on speech and emotion
Describing the emotional states that are expressed in speech
Speech Communication - Special issue on speech and emotion
2005 Special Issue: The interaction of attention and emotion
Neural Networks - Special issue: Emotion and brain
Emotion in speech: towards an integration of linguistic, paralinguistic, and psychological analysis
ICANN/ICONIP'03 Proceedings of the 2003 joint international conference on Artificial neural networks and neural information processing
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Emotional experience has two distinct components in human beings: 'automatic' and 'attended'. The former of these is based more heavily on the ventral and limbic areas of the brain; the attention part is concerned with cognitive aspects of experience, and involves more dorsal components. A rapidly increasing body of knowledge on these two separate components of human experience is being developed through brain imaging, single cell recording and deficit analyses under emotional as compared to neutral inputs. We start by summarizing this data. We then incorporate the data into a recently developed engineering control model of attention and motor responses. The crucial extension of this model involves a ventral/limbic brain network building representations of salience and valence. A simulation of a simple paradigm is used to demonstrate the considerable dissociation possible between the cognitive and emotional components. The system is further extended by inclusion of the attention-based CODAM model of consciousness. This allows us to relate 'emotions' to 'feelings' and delineate expected architectures for the construction of artificial emotional recognition systems.