Journal of East China Normal University(Natural Science) >

2020 , Vol. 2020 >Issue 6: 129 - 139

DOI: https://doi.org/10.3969/j.issn.1000-5641.201921017

Computer Science

Research on a Tang Poetry automatic generation system based on an evolutionary algorithm

  • MU Zhaonan ,
  • LIU Mengzhu ,
  • SUN Jieping ,
  • WANG Cheng
Expand
  • 1. College of Computer and Information Engineering, Guizhou University of Commerce, Guiyang 550014, China;
    2. College of Computer Science, Sichuan University, Chengdu 610207, China;
    3. Guangzhou Huizhi Communication Technology Co., Ltd, Guangzhou 510630, China

Received date: 2019-08-27

  Online published: 2020-12-01

Fold

Abstract

In this paper, research on an automatic generation algorithm for Tang poetry, one of the poetry genres, is carried out. The research work consists of the GloVe(Global Vectors for Word Representation) model to train-word vectors, an initial population scheme based on keywords and peaceful rhymes, a fitness function for grammatical and semantic weights, and a selection strategy used in tournament algorithms; the latter includes heuristic crossover and heuristic mutation operators as well as automatic generation of Tang poetry based on an evolutionary algorithm. Experiments show that by providing keywords the established model and system can achieve the initial goal for automatic generation of Tang poems. After manual modification, the proposed system can generate valuable and appreciable Tang poems.

Key words： evolutionary algorithms; automatic generation; Tang Poetry; natural language processing

Cite this article

MU Zhaonan , LIU Mengzhu , SUN Jieping , WANG Cheng . Research on a Tang Poetry automatic generation system based on an evolutionary algorithm[J]. Journal of East China Normal University(Natural Science), 2020 , 2020(6) : 129 -139 . DOI: 10.3969/j.issn.1000-5641.201921017

References

[1] 张建华, 陈家骏. 自然语言生成综述 [J]. 计算机应用研究, 2006, 23(8): 1-3, 13
[2] CHENG W F, WU C C, SONG R H, et al. Image inspired poetry generation in XiaoIce[EB/OL]. (2018-08-09)[2019-06-20]. https://arxiv.org/pdf/1808.03090.pdf.
[3] YU L T, ZHANG W N, WANG J, et al. SeqGAN: Sequence generative adversarial nets with policy gradient[EB/OL]. (2017-08-25)[2019-06-20]. https://arxiv.org/pdf/1609.05473.pdf.
[4] 游维. 基于遗传算法的宋词自动生成研究 [D]. 福建 厦门: 厦门大学, 2007.
[5] 周昌乐, 游维, 丁晓君. 一种宋词自动生成的遗传算法及其机器实现 [J]. 软件学报, 2010, 21(3): 427-437
[6] 曹卫华. 基于进化策略的仿唐诗自动生成系统 [D]. 广州: 广东工业大学, 2011.
[7] 穗志方, 俞士汶, 罗凤珠. 宋代名家诗自动注音研究及系统实现 [J]. 中文信息学报, 1998, 12(2): 44-53
[8] 冯思齐, 吕钢. 利用RNN模型生成中国古典诗歌 [J]. 通讯世界, 2018(2): 361-363
[9] 刘铮扬. 基于深度学习的中国诗歌自动生成算法研究 [D]. 长沙: 湖南师范大学, 2018.
[10] 潘正君, 康立山, 陈毓屏. 演化算法 [M]. 北京：清华大学出版社，1998.
[11] 彭定求, 沈三曾, 杨中讷, 等. 全唐诗 [M]. 北京: 中华书局, 2018.
[12] MITCHELL M. An Introduction to Genetic Algorithms [M]. Cambridge: MIT Press, 1998.
[13] 葛继科, 邱玉辉, 吴春明, 等. 遗传算法研究综述 [J]. 计算机应用研究, 2008, 25(10): 2911-2916
[14] 俞士汶, 段慧明, 朱学锋, 等. 北京大学现代汉语语料库基本加工规范 [J]. 中文信息学报, 2002, 16(5): 46-64
[15] 张忠纲. 全唐诗大辞典 [M]. 北京: 语文出版社, 2000.
[16] 朱武. 基于种群自适应策略的差分演化算法及其应用研究 [D]. 上海: 东华大学, 2013.
[17] 叶汝骏. 论唐代的仄韵五律—兼论仄韵律诗的归属问题 [J]. 武陵学刊, 2017, 42(3): 91-95
[18] 张冬茉, 葛永, 姚天昉. 多语种自然语言生成系统中的预映射句子规划器[D]. 北京: 北京大学, 2004
[19] 胡俊峰, 俞士汶. 唐宋始中词汇语义相似度的统计分析及应用 [J]. 中文信息学报, 2002, 16(4): 39-44
[20] 易勇. 计算机辅助诗词创作中的风格辨析及联语应对研究 [D]. 重庆: 重庆大学, 2005.
Options
Outlines

/

〈 〉