@inproceedings{zang-etal-2019-automated,
    title = "Automated Chess Commentator Powered by Neural Chess Engine",
    author = "Zang, Hongyu  and
      Yu, Zhiwei  and
      Wan, Xiaojun",
    editor = "Korhonen, Anna  and
      Traum, David  and
      M{\`a}rquez, Llu{\'i}s",
    booktitle = "Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics",
    month = jul,
    year = "2019",
    address = "Florence, Italy",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/fix-sig-urls/P19-1597/",
    doi = "10.18653/v1/P19-1597",
    pages = "5952--5961",
    abstract = "In this paper, we explore a new approach for automated chess commentary generation, which aims to generate chess commentary texts in different categories (e.g., \textit{description}, \textit{comparison}, \textit{planning}, etc.). We introduce a neural chess engine into text generation models to help with encoding boards, predicting moves, and analyzing situations. By jointly training the neural chess engine and the generation models for different categories, the models become more effective. We conduct experiments on 5 categories in a benchmark Chess Commentary dataset and achieve inspiring results in both automatic and human evaluations."
}