Artificial Emotion Engine Benchmark Problem Based on Psychological Test Paradigm

Wang Yi, Wang Zhi-liang


Most of testing and evaluations of emotion model in the field of affective computing are self-evaluation, which aims at the application-specific background, while the research on the problem of the Benchmark emotional model is scarce. This paper firstly proposed the feasibility of making psychological test paradigm a part of artificial Benchmark engine, and with taking versatility and effectiveness as the evolutional factor to judge the engine by testing psychological paradigms. In addition, an emotional hidden Markov model is built and tested based on the Benchmark theory. The detailed simulation process of the experiment is given.  The testing resultants are coincide with the real world’s situation.




Affective Computing; Artificial Emotion; Benchmark; Hidden Markov Model

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