@inproceedings{howcroft-etal-2018-toward,
    title = "Toward {B}ayesian Synchronous Tree Substitution Grammars for Sentence Planning",
    author = "Howcroft, David M.  and
      Klakow, Dietrich  and
      Demberg, Vera",
    editor = "Krahmer, Emiel  and
      Gatt, Albert  and
      Goudbeek, Martijn",
    booktitle = "Proceedings of the 11th International Conference on Natural Language Generation",
    month = nov,
    year = "2018",
    address = "Tilburg University, The Netherlands",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/jlcl-multiple-ingestion/W18-6546/",
    doi = "10.18653/v1/W18-6546",
    pages = "391--396",
    abstract = "Developing conventional natural language generation systems requires extensive attention from human experts in order to craft complex sets of sentence planning rules. We propose a Bayesian nonparametric approach to learn sentence planning rules by inducing synchronous tree substitution grammars for pairs of text plans and morphosyntactically-specified dependency trees. Our system is able to learn rules which can be used to generate novel texts after training on small datasets."
}