{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,25]],"date-time":"2026-03-25T15:52:30Z","timestamp":1774453950798,"version":"3.50.1"},"reference-count":22,"publisher":"Springer Science and Business Media LLC","issue":"2","license":[{"start":{"date-parts":[[2024,3,1]],"date-time":"2024-03-01T00:00:00Z","timestamp":1709251200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/2.zoppoz.workers.dev:443\/https\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2024,3,1]],"date-time":"2024-03-01T00:00:00Z","timestamp":1709251200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/2.zoppoz.workers.dev:443\/https\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62103103"],"award-info":[{"award-number":["62103103"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004608","name":"Natural Science Foundation of Jiangsu Province","doi-asserted-by":"publisher","award":["BK20210223"],"award-info":[{"award-number":["BK20210223"]}],"id":[{"id":"10.13039\/501100004608","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Neural Process Lett"],"abstract":"<jats:title>Abstract<\/jats:title><jats:p>Machine poetry generation has been studied for decades, among which ancient Chinese poetry is still challenging in the field of poetry generation due to its unique regularity and rhythm. The quality improvement of ancient Chinese poetries is one of the most promising research areas of ancient Chinese Natural Language Processing. This paper proposes an ancient Chinese poetry polishing model, which is used for polishing to obtain high-quality ancient Chinese poetry. The model consists of a detection network and a correction network. The detection network based on BiLSTM and CRF is used to detect different types of low-quality words in poems. The correction network based on the BERT model is used to modify the detected low-quality words in the global context. The polishing process is iteratively performed until the model judges that there are no low-quality words in the poem. The results show that the polished poems are improved in multiple evaluations. Compared with existing polishing models, the model proposed in this paper performs better in both automatic evaluation and human evaluation when the number of parameters is reduced.<\/jats:p>","DOI":"10.1007\/s11063-024-11480-9","type":"journal-article","created":{"date-parts":[[2024,3,1]],"date-time":"2024-03-01T14:02:01Z","timestamp":1709301721000},"update-policy":"https:\/\/2.zoppoz.workers.dev:443\/https\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["A Polishing Model for Machine-Generated Ancient Chinese Poetry"],"prefix":"10.1007","volume":"56","author":[{"given":"Zhe","family":"Chen","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yang","family":"Cao","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2024,3,1]]},"reference":[{"key":"11480_CR1","unstructured":"Devlin, J. Chang, M. Lee, K. Toutanova, (2019) K: BERT: Pre-training of deep bidirectional transformers for language understanding. In: North American Association for Computational Linguistics (NAACL), pp. 4147\u20134186"},{"issue":"3\u20134","key":"11480_CR2","doi-asserted-by":"publisher","first-page":"181","DOI":"10.1016\/S0950-7051(01)00095-8","volume":"14","author":"P Gerv\u00e1s","year":"2001","unstructured":"Gerv\u00e1s P (2001) An expert system for the composition of formal Spanish poetry. Knowl Based Syst 14(3\u20134):181\u2013188","journal-title":"Knowl Based Syst"},{"key":"11480_CR3","unstructured":"Manurung, H.: (2003) An evolutionary algorithm approach to poetry generation. In: Ph.D. Thesis, University of Edinburgh"},{"key":"11480_CR4","doi-asserted-by":"crossref","unstructured":"He, J. Zhou, M. Jiang, L.: (2012) Generating Chinese classical poems with statistical machine translation models. In: Proceedings of the 26th AAAI Conference on Artificial Intelligence, pp. 1650\u20131656","DOI":"10.1609\/aaai.v26i1.8344"},{"key":"11480_CR5","doi-asserted-by":"crossref","unstructured":"Zhang, X. Lapata, M.: (2014) Chinese poetry generation with recurrent neural networks. In: Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing, pp. 670\u2013680","DOI":"10.3115\/v1\/D14-1074"},{"key":"11480_CR6","unstructured":"Wang, Z. He, W. Wu, H. Wu, H. Li, W. Wang, H. Chen, E.: (2016) Chinese poetry generation with planning based neural network. In: Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers, pp. 1051\u20131060"},{"key":"11480_CR7","doi-asserted-by":"crossref","unstructured":"Huang, C. Lu, K. Cheng, Y. Peng, Y.: (2020) Generating Chinese Classical Poetry with Quatrain Generation Model QGM Using Encoder-Decoder LSTM. In: IEEE BigData, pp. 5700\u20135702","DOI":"10.1109\/BigData50022.2020.9378383"},{"key":"11480_CR8","doi-asserted-by":"crossref","unstructured":"Yi, X. Li, R. Sun, M.: (2017) Generating Chinese classical poems with RNN encoder-decoder. In: Chinese Computational Linguistics and Natural Language Processing Based on Naturally Annotated Big Data, pp. 211\u2013223","DOI":"10.1007\/978-3-319-69005-6_18"},{"key":"11480_CR9","doi-asserted-by":"crossref","unstructured":"Yi, X. Sun, M. Li, R. Yang, Z.: (2018) Chinese poetry generation with a working memory model. In: IJCAI, pp. 4553\u20134559","DOI":"10.24963\/ijcai.2018\/633"},{"key":"11480_CR10","doi-asserted-by":"crossref","unstructured":"Luo,Y. Li, C. Huang, C. Xu, C. Zeng, X. Wei, B. Xiao,T. Zhu, J: (2021) Chinese Poetry Generation with Metrical Constraints. In NLPCC, pp. 377\u2013388","DOI":"10.1007\/978-3-030-88480-2_30"},{"key":"11480_CR11","unstructured":"Yan, R.: I, poet: (2016) Automatic poetry composition through recurrent neural networks with iterative polishing schema. In: IJCAI, pp. 2238\u20132244"},{"key":"11480_CR12","doi-asserted-by":"publisher","first-page":"107409","DOI":"10.1016\/j.knosys.2021.107409","volume":"232","author":"T Gao","year":"2021","unstructured":"Gao T, Zhu S, Liu J, Shen J, Shen J, Yang S, Xiong S (2021) A new context-aware approach for automatic Chinese poetry generation. In Knowledge-Based Syst 232:107409","journal-title":"In Knowledge-Based Syst"},{"key":"11480_CR13","doi-asserted-by":"crossref","unstructured":"Gao, T. Xiong, P. Shen, J.: (2020) A new automatic Chinese poetry generation Model based on neural network. In SERVICES, pp. 41\u201344","DOI":"10.1109\/SERVICES48979.2020.00023"},{"key":"11480_CR14","doi-asserted-by":"crossref","unstructured":"Deng, L. Wang, J. Liang, H. Chen, H. Xie, Z. Zhuang, B. Wang, S. Xiao, J.: (2020) An iterative polishing framework based on quality aware masked language model for Chinese poetry generation. In: AAAI2020, pp. 7643\u20137650","DOI":"10.1609\/aaai.v34i05.6265"},{"key":"11480_CR15","unstructured":"Vaswani, A. Shazeer, N. Parmar, N. Uszkoreit, J. Jones, L. Gomez, A. Kaiser, L. Polosukhin, I.: (2017) Attention is all you need. In Advances in Neural Information Processing Systems, pp. 6000\u20136010"},{"key":"11480_CR16","doi-asserted-by":"crossref","unstructured":"Zhang, S. Huang, H. Liu, J. Li, H.: (2020) Spelling Error Correction with Soft-Masked BERT. In: ACL, pp. 882\u2013890","DOI":"10.18653\/v1\/2020.acl-main.82"},{"key":"11480_CR17","unstructured":"Kingma, D. Ba, J.: (2015) Adam:\u00a0A\u00a0Method\u00a0for\u00a0Stochastic\u00a0Optimization. In: ICLR"},{"key":"11480_CR18","unstructured":"Guo, Z. Yi, X. Sun, M. Li, W. Yang, C. Liang, J. Chen, H. Zhang, Y. Li, R.: (2019) Jiuge: A Human-Machine Collaborative Chinese Classical Poetry Generation System. In: Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics: System Demonstrations, pp. 25\u201330"},{"key":"11480_CR19","doi-asserted-by":"publisher","first-page":"9450","DOI":"10.1609\/aaai.v34i05.6488","volume":"2020","author":"X Yi","year":"2020","unstructured":"Yi X, Li R, Yang C, Li W, Sun M (2020) MixPoet: Diverse poetry generation via learning controllable mixed latent space. In Proceedings of AAAI 2020:9450\u20139457","journal-title":"In Proceedings of AAAI"},{"key":"11480_CR20","doi-asserted-by":"crossref","unstructured":"Papineni, K., Roukos, S., Ward, T., Zhu, W.: BLEU: (2002) A method for automatic evaluation of machine translation. In: Proceedings of ACL, pp. 311\u2013318","DOI":"10.3115\/1073083.1073135"},{"key":"11480_CR21","unstructured":"Wieting, J. Bansal, M. Gimpel, K. Livescu, K.: (2016) Towards universal paraphrastic sentence embeddings. In: ICLR"},{"key":"11480_CR22","doi-asserted-by":"crossref","unstructured":"Li, J. Song, Y. Zhang, H. Chen, D. Shi, S. Zhao, D. Yan, R.: (2018) Generating classical Chinese poems via conditional variational autoencoder and adversarial training. In: Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, pp. 3890\u20133900","DOI":"10.18653\/v1\/D18-1423"}],"container-title":["Neural Processing Letters"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/2.zoppoz.workers.dev:443\/https\/link.springer.com\/content\/pdf\/10.1007\/s11063-024-11480-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/2.zoppoz.workers.dev:443\/https\/link.springer.com\/article\/10.1007\/s11063-024-11480-9\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/2.zoppoz.workers.dev:443\/https\/link.springer.com\/content\/pdf\/10.1007\/s11063-024-11480-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,5,16]],"date-time":"2024-05-16T20:29:25Z","timestamp":1715891365000},"score":1,"resource":{"primary":{"URL":"https:\/\/2.zoppoz.workers.dev:443\/https\/link.springer.com\/10.1007\/s11063-024-11480-9"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,3,1]]},"references-count":22,"journal-issue":{"issue":"2","published-online":{"date-parts":[[2024,4]]}},"alternative-id":["11480"],"URL":"https:\/\/2.zoppoz.workers.dev:443\/https\/doi.org\/10.1007\/s11063-024-11480-9","relation":{},"ISSN":["1573-773X"],"issn-type":[{"value":"1573-773X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,3,1]]},"assertion":[{"value":"17 October 2023","order":1,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"1 March 2024","order":2,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare no competing interests.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}],"article-number":"77"}}