Abstract
This paper presents a novel statistical Natural Language Generation (NLG) approach relying on language models (Positional and Factored Language Models). To prove and validate our approach, we carried out a series of experiments in the scenario of story generation. Through the different configurations tested, our NLG approach is able to produce either a regeneration in the form of a summary of the original story, or a recreation of one story, i.e., a new story based on the entities and actions that the original narration conveys, showing its flexibility to produce different types of stories. The results obtained and the subsequent analysis of the generated stories shows that the macroplanning addressed in this manner is a key step in the process of NLG, improving the quality of the story generated, and decreasing the error rate with respect to not including this stage.
This research work has been partially funded by the Generalitat Valenciana, by the grant ACIF/2016/501, and the Spanish Government through the projects PROMETEOII/2014/001, TIN2015-65100-R, and TIN2015-65136-C2-2-R.
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Bilmes, J.A., Kirchhoff, K.: Factored language models and generalized parallel backoff. In: Companion Volume of the Proceedings of HLT-NAACL, pp. 4–6 (2003)
Isard, A., Brockmann, C., Oberlander, J.: Individuality and alignment in generated dialogues. In: Proceedings of the INLG Conference, pp. 25–32. ACL (2006)
Lin, C.Y.: Rouge: A package for automatic evaluation of summaries. In: Text Summarization Branches Out: Proceedings, pp. 74–81. ACL (2004)
Liu, S.H., Chen, K.Y., Chen, B., Wang, H.M., Yen, H.C., Hsu, W.L.: Positional language modeling for extractive broadcast news speech summarization. In: INTERSPEECH, pp. 2729–2733 (2015)
Lukin, S.M., Reed, L.I., Walker, M.A.: Generating sentence planning variations for story telling. In: 16th SIGDIAL, p. 188 (2015)
Lv, Y., Zhai, C.: Positional language models for information retrieval. In: Proceedings of the 32nd International ACM SIGIR, pp. 299–306. ACM (2009)
Mairesse, F., Young, S.: Stochastic language generation in dialogue using factored language models. Comput. Linguist. 40(4), 763–799 (2014)
Novais, E.M., Paraboni, I.: Portuguese text generation using factored language models. J. Braz. Comput. Soc. 19(2), 135–146 (2012)
Padró, L., Stanilovsky, E.: Freeling 3.0: towards wider multilinguality. In: Proceedings of LREC 2012. European Language Resources Association (2012)
Snover, M., Dorr, B., Schwartz, R., Micciulla, L., Makhoul, J.: A study of translation edit rate with targeted human annotation. In: Proceedings of AMTA, pp. 223–231 (2006)
Winer, D.R., Young, R.M.: Discourse-driven narrative generation with bipartite planning. In: Proceedings of the 9th INLG Conference, pp. 11–20 (2016)
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Vicente, M., Barros, C., Lloret, E. (2017). A Study on Flexibility in Natural Language Generation Through a Statistical Approach to Story Generation. In: Frasincar, F., Ittoo, A., Nguyen, L., Métais, E. (eds) Natural Language Processing and Information Systems. NLDB 2017. Lecture Notes in Computer Science(), vol 10260. Springer, Cham. https://doi.org/10.1007/978-3-319-59569-6_57
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DOI: https://doi.org/10.1007/978-3-319-59569-6_57
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