Multi-events Driven Emotion Dynamic Generation Using Hawkes Process

Abstract

Multi-events driven emotion generation was an important research point in the affective computing field. However, as the events have different types and occurred in variable times, then computing the emotion state intensity became a challenge. The existed solutions for this problem did not take time influences of different event types into consideration. In order to solve this problem, we provided a Hawkes process based multi-events driven emotion generation method. Firstly we appraised every event and generate the related emotional reaction; secondly, we treated the emotion generation process with a certain period as a point process and trained the parameters of Hawkes process by maximum likelihood estimation with real individual emotional reactions; thirdly, we used Hawkes process to simulate the accumulated emotion reactions. The experimental results showed that our method can generate a multi-events driven emotion more accurately and efficiently.