Affective computing
An advanced mental state transition network and psychological experiments
EUC'05 Proceedings of the 2005 international conference on Embedded and Ubiquitous Computing
Construction of a blog emotion corpus for Chinese emotional expression analysis
EMNLP '09 Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing: Volume 3 - Volume 3
Information Processing and Management: an International Journal
Estimation of word emotions based on part of speech and positional information
Computers in Human Behavior
Employing hierarchical Bayesian networks in simple and complex emotion topic analysis
Computer Speech and Language
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Information recognition and extraction of human emotions are necessary for machines to communicate smoothly with humans and to realize emotion communications. We focus on human psychological characteristics to develop general-purpose agents that can recognize human emotion and create machine emotion. We comprehensively analyze brain waves, voice sounds and picture images that represent information included in emotion elements of phonation, facial expressions, and speech usage. We analyze and estimate many statistical data based on the latest achievements of brain science and psychology in order to derive transition networks for human psychological states. We establish a speaker word model for researching computer simulation of psychological change and emotional presentation, developing emotion interface, and establishing theoretic structure and realization method of emotion communication. A new approach for recognizing human emotion based on Mental State Transition Network will be described and one emotion estimation method based on sentence pattern of emotion occurrence events will be discussed, and some new results of the project will be given.