一种基于Hawkes过程的隐藏情绪倾向识别方法

为有效模拟情绪的动态转换过程，检测个体在交互过程中隐藏的情绪倾向从而提高虚拟交互过程的智能性，首先利用Hawkes过程模拟个体情绪的产生与衰退过程，然后利用隐马尔科夫模型检测个体的表情并将其映射到情绪模型的维度空间，最后通过对比受到事件刺激前后观测到的情绪状态来推导个体针对事件的情绪倾向.在个体隐藏情绪状态的情况下，系统采用持续追加正向刺激的策略激活个体的情绪表达，对于无法检测到情绪表达的状态采用默认为负倾向的策略.实验显示，本方法能够有效计算个体隐藏的情绪倾向并提高交互的智能性. 

A Hidden Sentiment Detection Method Based on Hawkes Process

In order to simulate the dynamic transformation process of emotion effectively and detect the hidden sentiment of individuals in the interaction process, so as to improve the intelligence of virtual interaction process, a Hawkes process was used to simulate the process of individual emotion generation and decline firstly. Then the individual''s expression was detected by the hidden Markov model and mapped to the dimensional space of the emotional model. Finally, the sentiment of the individual was derived by comparing the emotional states that observed after and before the event stimulus. In the case when an individual hidden the emotional states, a strategy, continually appending positive stimulation to the individual, was introduced to activate the emotional expressions, and adopted the negative as the default sentiment for the unsuccessful detection of the emotional expressions. Experiments show that, this method can effectively calculate individual''s hidden sentiment and improve the intelligence of interaction.