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| Maximum Similarity Matching Emotion Model Based on Mapping between State Space and Probability Space |
| WANG Hao,ZHANG Quan-Yi,FANG Bao-Fu,FANG Shuai |
| School of Computer and Information,Hefei University of Technology,Hefei 23009 |
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Abstract Robot emotion modeling is a hot issue in emotion robot research. Based on the emotion psychology knowledge,a dynamic emotion transfer model of the emotion robot is presented with different personalities under different external stimulation. The influences of personality and external stimulation are discussed. The emotion model based on state space is used to describe the emotion states of robot. The emotiontransfer process is simulated by hidden Markov model (HMM) process. However,the HMM process can only work out the current probability of the emotion state. To get the concrete emotion state,the maximum similarity matching emotion transfer model based on mapping between state space and probability space is proposed. Firstly,the current emotion probability is calculated by HMM process. Then,the current concrete emotion state is obtained by maximum similarity matching. Different personalities and stimulation can be built by adjusting the parameters of the model. The proposed model simulates the transformation process effectively. The experimental results show that the emotion transfer process simulated by the proposed model corresponds with the general rules of human emotion transformation.
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Received: 06 June 2012
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2013, Vol. 26 
