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计算机系统应用:2020,29(5):46-51
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更具有感情色彩的诗歌生成模型
(上海应用技术大学 电子信息工程系, 上海 201418)
Poetry Generation Model with More Emotional Information
(Department of Electronic Information Engineering, Shanghai Institute of Technology, Shanghai 201418, China)
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投稿时间:2019-09-03    修订日期:2019-10-08
中文摘要: 五言绝句是我们传统文学的宝藏,给人独特的语言美感和审美体验.使用机器生成绝句诗歌对机器理解人类语言有着积极的探索意义.依据诗歌语言自身韵律和对仗特点,我们在诗歌数据集和对联数据集上联合训练诗歌生成模型.模型包括语义模型和文字规则模型,语义模型创新性地使用一维卷积网络提取诗歌文字的语义特征,学习诗歌语义的主题信息.文字规则模型使用带注意力机制的编码解码器,学习诗歌文字的对仗特征.实验结果表明模型可以很好地生成符合诗歌规则,表现诗人情感的诗句,如“感时花溅泪,愁路竹林心.秋风草树色,夜雨寒风声.”
Abstract:The five-character quatrain is the treasure of Chinese traditional literature, rendering people a unique language aesthetic and aesthetic experience. The process of machine-generated quatrain has a positive exploration of machine acquisition on human language. Inspired by the rhythm and antithesis features of poetry language itself, we trained language memory model on poetry datasets and couplet datasets. The model consists of a semantic model and a textual rule model. The semantic model uses a one-dimensional convolution network to extract the semantic features of poetry and learn the semantic information of the poetry. The word model uses an encoder-decoder model with attention mechanism to learn the isocolon features of poetry writing. The experimental results show the language memory model can generate poems that conform to the rules of poetry and our aesthetics.
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廖荣凡,沈希忠,刘爽.更具有感情色彩的诗歌生成模型.计算机系统应用,2020,29(5):46-51
LIAO Rong-Fan,SHEN Xi-Zhong,LIU Shuang.Poetry Generation Model with More Emotional Information.COMPUTER SYSTEMS APPLICATIONS,2020,29(5):46-51

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