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Composing Like an Ancient Chinese Poet: Learn to Generate Rhythmic Chinese Poetry

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Abstract

Automatic generation of Chinese classical poetry is still a challenging problem in artificial intelligence. Recently, Encoder-Decoder models have provided a few viable methods for poetry generation. However, by reviewing the prior methods, two major issues still need to be settled: 1) most of them are one-stage generation methods without further polishing; 2) they rarely take into consideration the restrictions of poetry, such as tone and rhyme. Intuitively, some ancient Chinese poets tended first to write a coarse poem underlying aesthetics and then deliberated its semantics; while others first create a semantic poem and then refine its aesthetics. On this basis, in order to better imitate the human creation procedure of poems, we propose a two-stage method (i.e., restricted polishing generation method) of which each stage focuses on the different aspects of poems (i.e., semantics and aesthetics), which can produce a higher quality of generated poems. In this way, the two-stage method develops into two symmetrical generation methods, the aesthetics-to-semantics method and the semantics-to-aesthetics method. In particular, we design a sampling method and a gate to formulate the tone and rhyme restrictions, which can further improve the rhythm of the generated poems. Experimental results demonstrate the superiority of our proposed two-stage method in both automatic evaluation metrics and human evaluation metrics compared with baselines, especially in yielding consistent improvements in tone and rhyme.

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Author notes

  1. Co-First Author (Ming He and Yan Chen contributed equally to this work. Ming He mainly contributed to the method (RPG) designing and paper writing, and Yan Chen mainly contributed to the method (RPG) optimization and experiments realization.)

Authors and Affiliations

  1. Department of Electronic Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China

    Ming He & Gui-Hua Zeng

  2. AI Laboratory, Lenovo Research, Beijing, 100193, China

    Ming He

  3. Baidu Incorporated, Beijing, 100193, China

    Yan Chen

  4. College of Management and Economics, Tianjin University, Tianjin, 300072, China

    Hong-Ke Zhao

  5. School of Computer Science and Technology, University of Science and Technology of China, Hefei, 230027, China

    Qi Liu & Gui-Quan Liu

  6. School of Computer Science and Information Engineering, Hefei University of Technology, Hefei, 230009, China

    Le Wu

  7. Risk Control Department, OPay, Beijing, 100010, China

    Yu Cui

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  1. Ming He
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  3. Hong-Ke Zhao
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  4. Qi Liu
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Correspondence to Gui-Hua Zeng.

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He, M., Chen, Y., Zhao, HK. et al. Composing Like an Ancient Chinese Poet: Learn to Generate Rhythmic Chinese Poetry. J. Comput. Sci. Technol. 38, 1272–1287 (2023). https://doi.org/10.1007/s11390-023-1295-1

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