A Preliminary Study for Literary Rhyme Generation based on Neuronal Representation, Semantics and Shallow Parsing

  • Luis-Gil Moreno-Jiménez Avignon Université
  • Juan-Manuel Torres-Moreno Avignon Université
  • Roseli S. Wedemann UERJ


In recent years, researchers in the area of Computational Creativity have studied the human creative process proposing different approaches to reproduce it with a formal procedure. In this paper, we introduce a model for the generation of literary rhymes in Spanish, combining structures of language and neural network models The results obtained with a manual evaluation of the texts generated by our algorithm are encouraging.


Agirrezabal, M., Arrieta, B., Astigarraga, A., and Hulden, M. (2013). Pos-tag based poetry generation with WordNet. In European Workshop on NLG ’13, pages 162–166, Sofia, Bulgaria. ACL.

Bengio, Y., Courville, A., and Vincent, P. (2013). Representation learning: A review and new perspectives. IEEE Transactions on Pattern Analysis and Machine Intelligence, 35(8):1798–1828.

Boden, M. A. (2004). The creative mind: Myths and Mechanisms. Routledge.

Bracewell, D., Ren, F., and Kuriowa, S. (2005). Multilingual single document keyword In Proc. ICNLPK’ 05, pages 517–522, Wuhan, extraction for information retrieval. China. IEEE.

Clark, E., Ji, Y., and Smith, N. A. (2018). Neural text generation in stories using entity representations as context. In Proc. NACACL-HLT ’18, volume 1, pages 2250–2260, New Orleans, Louisiana.

Kiddon, C., Zettlemoyer, L., and Choi, Y. (2016). Globally coherent text generation with neural checklist models. In Proc. EMNLP ’16, pages 329–339, Austin, Texas. Association for Computational Linguistics.

Medina Urrea, A. (2018). Diccionario de rimas asonantes y consonantes del español de México. El Colegio de México, Mexico.

Mikolov, T., Chen, K., Corrado, G., and Dean, J. (2013a). Efficient estimation of word representations in vector space. In Bengio, Y. and LeCun, Y., editors, ICLR ’13, Scottsdale, Arizona, USA. ICLR.

Mikolov, T., Yih, W.-t., and Zweig, G. (2013b). Linguistic regularities in continuous space word representations. In NACACL-HLT ’13, pages 746–751, Atlanta, USA.

Molins, P. and Lapalme, G. (2015). JSrealB: A bilingual text realizer for web programming. In Proc. ENLG ’15, pages 109–111, Brighton, UK. ACL.

Moreno-Jiménez, L.-G., Torres-Moreno, J.-M., and Wedemann, R. S. (2020a). Literary In Proc. NLPIS ’20, LNCS, natural language generation with psychological traits. volume 12089, pages 193–204, Cham. Springer.

Moreno-Jiménez, L.-G., Torres-Moreno, J.-M., Wedemann, R. S., and SanJuan, E. (2020b). Generación automática de frases literarias. Linguamática, 12(1):15–30.

Moreno-Jiménez, L.-G. and Torres-Moreno, J.-M. (2021). Megalite: A New Spanish Literature Corpus for NLP Tasks. In David C. Wyld, D. N. E., editor, Proc. AIAP ’21, Zurich, Switzerland.

Oliveira, H. G. (2017). A survey on intelligent poetry generation: Languages, features, techniques, reutilisation and evaluation. In Proc. ICNLG ’17, pages 11–20.

Oliveira, H. G. and Cardoso, A. (2015). Poetry generation with PoeTryMe. In Proc. CCR-TCM ’15, volume 7, Paris. Atlantis Thinking Machines.

Padró, L. and Stanilovsky, E. (2012). FreeLing 3.0: Towards wider multilinguality. In Proc. of the 8th on LREC ’12, pages 2473–2479, Istanbul, Turkey.

Torres-Moreno, J.-M. (2012). Beyond stemming and lemmatization: Ultra-stemming to improve automatic text summarization. ArXiv, abs/1209.3126.

Urrea, A. M. and Torres-Moreno, J.-M. (2019). RIMAX: ranking semantic rhymes by calculating definition similarity. ArXiv, abs/1912.09558.

van Deemter, K., Theune, M., and Krahmer, E. (2005). Real versus template-based natural language generation: A false opposition? Computational Linguistics, 31(1):15–24.

Zhang, X. and Lapata, M. (2014). Chinese poetry generation with recurrent neural networks. In Proc. EMNLP ’14, pages 670–680, Doha, Qatar. ACL.
Como Citar

Selecione um Formato
MORENO-JIMÉNEZ, Luis-Gil; TORRES-MORENO, Juan-Manuel; WEDEMANN, Roseli S.. A Preliminary Study for Literary Rhyme Generation based on Neuronal Representation, Semantics and Shallow Parsing. In: SIMPÓSIO BRASILEIRO DE TECNOLOGIA DA INFORMAÇÃO E DA LINGUAGEM HUMANA (STIL), 13. , 2021, Evento Online. Anais [...]. Porto Alegre: Sociedade Brasileira de Computação, 2021 . p. 190-198. DOI: https://doi.org/10.5753/stil.2021.17798.