Title :
Pattern recognition of emotion with neural network
Author :
Yamada, Tomoaki ; Hashimoto, Hiroya ; Tosa, Naoko
Author_Institution :
Inst. of Ind. Sci., Tokyo Univ.
Abstract :
Proposes an emotion model for communication which also transfers personality and character information. The emotion model customizes to individual human communication partners by learning. Learning is achieved by neural networks converting input voice signals to an emotion state. The emotion state decides the response of the partner. The emotion state is divided into four categories: sadness; cheerfulness; happiness; and anger. For example, a loud voice causes the emotion of anger. This paper also discusses the emotion model as network agent between two human communication partners
Keywords :
behavioural sciences; behavioural sciences computing; human factors; learning (artificial intelligence); neural nets; speech recognition; Network Neuro-Baby; anger; character information; cheerfulness; emotion model; happiness; human communication; input voice signals; learning; neural network; pattern recognition; personality; response; sadness; Character generation; Education; Emotion recognition; Face recognition; Humans; Monitoring; Neural networks; Pattern recognition; Petroleum; Speech recognition;
Conference_Titel :
Industrial Electronics, Control, and Instrumentation, 1995., Proceedings of the 1995 IEEE IECON 21st International Conference on
Conference_Location :
Orlando, FL
Print_ISBN :
0-7803-3026-9
DOI :
10.1109/IECON.1995.483355
