Improving the emotional awareness of pre-trained language models is an emerging important problem for dialogue generation tasks. Although prior studies have introduced methods to improve empathetic dialogue generation, few have discussed how to incorporate commonsense knowledge into pre-trained language models for controllable dialogue generation. In this study, we propose a novel framework that improves empathetic dialogue generation using pre-trained language models by 1) incorporating commonsense knowledge through prompt verbalization, and 2) controlling dialogue generation using a strategy-driven future discriminator. We conducted experiments to reveal that both the incorporation of social commonsense knowledge and enforcement of control over generation help to improve generation performance. Finally, we discuss the implications of our study for future research.

翻译：提升预训练语言模型的情感感知能力是对话生成任务中一个日益重要的新兴问题。尽管已有研究提出了改进共情对话生成的方法，但鲜有研究讨论如何将常识知识融入预训练语言模型以实现可控对话生成。在本研究中，我们提出了一种新颖框架，通过以下两种方式改进基于预训练语言模型的共情对话生成：1）通过提示语词化融入常识知识；2）利用策略驱动的未来判别器控制对话生成。实验结果表明，融入社会常识知识及对生成过程施加控制均有助于提升生成性能。最后，我们讨论了本研究对未来研究的意义。