论文标题
让我们幽默：知识增强了幽默的产生
Let's be Humorous: Knowledge Enhanced Humor Generation
论文作者
论文摘要
幽默的产生是一个探索且具有挑战性的问题。先前的作品主要利用模板或替换短语来产生幽默。但是，很少有作品专注于自由形式和幽默的背景知识。幽默的语言理论将幽默句子的结构定义为设置和重点。在本文中，我们探讨了如何使用相关知识的设置来生成一键。我们提出了一个可以将知识融合到端到端模型的框架。据我们所知，这是使用知识增强模型生成打孔线的首次尝试。此外，我们创建了第一个幽默知识数据集。实验结果表明，我们的方法可以利用知识来产生流利，有趣的打孔线，这表现优于几个基线。
The generation of humor is an under-explored and challenging problem. Previous works mainly utilize templates or replace phrases to generate humor. However, few works focus on freer forms and the background knowledge of humor. The linguistic theory of humor defines the structure of a humor sentence as set-up and punchline. In this paper, we explore how to generate a punchline given the set-up with the relevant knowledge. We propose a framework that can fuse the knowledge to end-to-end models. To our knowledge, this is the first attempt to generate punchlines with knowledge enhanced model. Furthermore, we create the first humor-knowledge dataset. The experimental results demonstrate that our method can make use of knowledge to generate fluent, funny punchlines, which outperforms several baselines.
