汉语诗歌的显着线索生成机制
Chinese Poetry Generation with a Salient-Clue Mechanism
摘要：
中国诗歌作为人类文化遗产的宝贵组成部分，影响了一代又一代人。自动写诗对AI来说是一个挑战。近年来，得益于神经网络的发展，这一领域取得了重大进展。然而，作为一个整体，一首生成的诗歌在意义、主题甚至意境上的连贯性仍然是一个大问题。在本文中，我们提出了一个新的显着线索机制，中文诗歌生成。不同于以往的工作，试图利用所有的上下文信息，我们的模型自动选择最显着的字符从每一个迄今为止生成的行，逐步形成一个显着的线索，这是用来指导后续的诗歌生成过程，以消除中断，提高连贯性。此外，我们的模型可以灵活地扩展，以控制生成的诗歌在不同的方面，如诗歌风格，这进一步提高了连贯性。实验结果表明，我们的模型是非常有效的，优于三个强基线。
英文摘要：
As a precious part of the human cultural heritage, Chinese poetry has influenced people for generations. Automatic poetry composition is a challenge for AI. In recent years, significant progress has been made in this area benefiting from the development of neural networks. However, the coherence in meaning, theme or even artistic conception for a generated poem as a whole still remains a big problem. In this paper, we propose a novel Salient-Clue mechanism for Chinese poetry generation. Different from previous work which tried to exploit all the context information, our model selects the most salient characters automatically from each so-far generated line to gradually form a salient clue, which is utilized to guide successive poem generation process so as to eliminate interruptions and improve coherence. Besides, our model can be flexibly extended to control the generated poem in different aspects, for example, poetry style, which further enhances the coherence. Experimental results show that our model is very effective, outperforming three strong baselines.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
