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Multi-events Driven Emotion Dynamic Generation Using Hawkes Process

机译:多赛量驱动的情绪动态生成使用鹰过程

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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.
机译:多事件驱动的情感生成是情感计算领域的一个重要研究点。然而,由于事件具有不同类型并且发生在可变时间中,因此计算情绪状态强度成为挑战。本问题存在的解决方案并未考虑不同事件类型的时间影响。为了解决这个问题,我们提供了一种基于霍克斯进程的多事件驱动情感生成方法。首先,我们评估了每次活动并产生相关的情绪反应;其次,我们将情绪生成过程视为一个时期作为点过程,通过具有真正的个人情绪反应的最大似然估计来训练霍克斯过程的参数;第三,我们使用Hawkes流程来模拟积累的情绪反应。实验结果表明,我们的方法可以更准确,有效地产生多事件驱动的情感。

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