论文标题
像人类一样构成：共同改善现代中国诗歌的连贯性和新颖性
Compose Like Humans: Jointly Improving the Coherence and Novelty for Modern Chinese Poetry Generation
论文作者
论文摘要
中国诗歌是全球文化的重要组成部分，古典和现代的子分支机构完全不同。前者是一种独特的类型，具有严格的限制，而后者的长度非常灵活，可选为押韵，并且类似于其他语言的现代诗歌。因此，它需要更多控制连贯性并改善新颖性。在本文中，我们提出了一个生成的retrieve-then-refine范式，以共同提高连贯性和新颖性。在第一阶段，仅生成一个给定关键字（即主题）的草稿。第二阶段从检索线产生“精炼矢量”。最后，我们考虑了草稿和“精炼矢量”来产生一首新诗。草案提供了将来的句子级信息，以生成一行。同时，“精炼矢量”指出了基于令人印象深刻的单词检测机制，可以从参考中学习良好的模式，然后通过插入操作创建新的模式。对收集的大规模现代中国诗歌数据集的实验结果表明，我们提出的方法不仅可以产生更连贯的诗歌，而且可以改善多样性和新颖性。
Chinese poetry is an important part of worldwide culture, and classical and modern sub-branches are quite different. The former is a unique genre and has strict constraints, while the latter is very flexible in length, optional to have rhymes, and similar to modern poetry in other languages. Thus, it requires more to control the coherence and improve the novelty. In this paper, we propose a generate-retrieve-then-refine paradigm to jointly improve the coherence and novelty. In the first stage, a draft is generated given keywords (i.e., topics) only. The second stage produces a "refining vector" from retrieval lines. At last, we take into consideration both the draft and the "refining vector" to generate a new poem. The draft provides future sentence-level information for a line to be generated. Meanwhile, the "refining vector" points out the direction of refinement based on impressive words detection mechanism which can learn good patterns from references and then create new ones via insertion operation. Experimental results on a collected large-scale modern Chinese poetry dataset show that our proposed approach can not only generate more coherent poems, but also improve the diversity and novelty.
