脑电模型:情绪社交分享的情绪情节生成

Ana Antunes, Joana Campos, João Dias, P. A. Santos, R. Prada
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引用次数: 1

摘要

情绪的社会分享(SSE)发生在一个人在社会互动过程中对某一事件的感受和反应进行交流时。这种现象是我们社会结构的一部分,在创造移情反应和建立融洽关系方面起着重要作用。具备SSE能力的智能社会代理将拥有与人类建立长期互动的机制。在本文中,我们提出了情绪事件生成(EEG)模型,这是一个经过微调的GPT-2模型,能够以类似人类的方式生成关于多个事件元组的情感社交对话。人类评估结果表明,该模型成功地将一个或多个事件元组转化为情感片段,达到接近人类表现的质量水平。此外,该模型在每一集中都清楚地表达了一种情感,就像人类一样。为了训练这个模型,我们使用了一个公共数据集,并在此基础上使用事件提取技术1。
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EEG Model: Emotional Episode Generation for Social Sharing of Emotions
Social sharing of emotions (SSE) occurs when one communicates their feelings and reactions to a certain event in the course of a social interaction. The phenomenon is part of our social fabric and plays an important role in creating empathetic responses and establishing rapport. Intelligent social agents capable of SSE will have a mechanism to create and build long-term interaction with humans. In this paper, we present the Emotional Episode Generation (EEG) model, a fine-tuned GPT-2 model capable of generating emotional social talk regarding multiple event tuples in a human-like manner. Human evaluation results show that the model successfully translates one or more event-tuples into emotional episodes, reaching quality levels close to human performance. Furthermore, the model clearly expresses one emotion in each episode as well as humans. To train this model we used a public dataset and built upon it using event extraction techniques1.
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