Algorithm Research & Explore
|
164-168

Chinese poetry generation model with multi-adversarial training

Huang Wenminga,b
Ren Chonga
Deng Zhenronga,b
a. College of Computer & Information Security, b. Guangxi Colleges & Universities Keys Laboratory of Cloud Computing & Complex Systems, Guilin University of Electronic Technology, Guilin Guangxi 541000, China

Abstract

Many generation methods still have a large gap from the human creation, especially on the aspects of topical relevance and semantics of verses. To address these shortcomings of existing methods, this paper proposed a framework for generating poems with multiple adversarial training. The poetry generator used the sequence-to-sequence model with the attention mechanism and dual-encoding. Two discriminative model guided the poetry generation, included hierarchical RNN and TextCNN. Meanwhile, the framework used policy gradient for multi-adversarial training. Experiments show that the poetry generation method based on multi-adversarial training effectively improves the relevance between verses and vision keywords, and the semantic connotation of poem is more abundant.

Foundation Support

广西自然科学基金资助项目(2018GXNSFAA138132)
桂林电子科技大学研究生教育创新计划资助项目(2019YCXS050)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2019.07.0515
Publish at: Application Research of Computers Printed Article, Vol. 38, 2021 No. 1
Section: Algorithm Research & Explore
Pages: 164-168
Serial Number: 1001-3695(2021)01-033-0164-05

Publish History

[2021-01-05] Printed Article

Cite This Article

黄文明, 任冲, 邓珍荣. 基于多对抗训练的古诗生成方法 [J]. 计算机应用研究, 2021, 38 (1): 164-168. (Huang Wenming, Ren Chong, Deng Zhenrong. Chinese poetry generation model with multi-adversarial training [J]. Application Research of Computers, 2021, 38 (1): 164-168. )

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  • Application Research of Computers Monthly Journal
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Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

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