Chinese Poetry Generation with a Salient-Clue Mechanism

Xiaoyuan Yi, Ruoyu Li, Maosong Sun


Abstract
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.
Anthology ID:
K18-1024
Volume:
Proceedings of the 22nd Conference on Computational Natural Language Learning
Month:
October
Year:
2018
Address:
Brussels, Belgium
Editors:
Anna Korhonen, Ivan Titov
Venue:
CoNLL
SIG:
SIGNLL
Publisher:
Association for Computational Linguistics
Note:
Pages:
241–250
Language:
URL:
https://aclanthology.org/K18-1024
DOI:
10.18653/v1/K18-1024
Bibkey:
Cite (ACL):
Xiaoyuan Yi, Ruoyu Li, and Maosong Sun. 2018. Chinese Poetry Generation with a Salient-Clue Mechanism. In Proceedings of the 22nd Conference on Computational Natural Language Learning, pages 241–250, Brussels, Belgium. Association for Computational Linguistics.
Cite (Informal):
Chinese Poetry Generation with a Salient-Clue Mechanism (Yi et al., CoNLL 2018)
Copy Citation:
PDF:
https://aclanthology.org/K18-1024.pdf