@inproceedings{luo-li-2020-yin,
    title = "引入源端信息的机器译文自动评价方法研究(Research on Incorporating the Source Information to Automatic Evaluation of Machine Translation)",
    author = "Luo, Qi  and
      Li, Maoxi",
    editor = "Sun, Maosong  and
      Li, Sujian  and
      Zhang, Yue  and
      Liu, Yang",
    booktitle = "Proceedings of the 19th Chinese National Conference on Computational Linguistics",
    month = oct,
    year = "2020",
    address = "Haikou, China",
    publisher = "Chinese Information Processing Society of China",
    url = "https://preview.aclanthology.org/fix-sig-urls/2020.ccl-1.38/",
    pages = "414--423",
    language = "zho",
    abstract = "机器译文自动评价是机器翻译中的一个重要任务。针对目前译文自动评价中完全忽略源语言句子信息,仅利用人工参考译文度量翻译质量的不足,该文提出了引入源语言句子信息的机器译文自动评价方法:从机器译文与其源语言句子组成的二元组中提取描述翻译质量的质量向量,并将其与基于语境词向量的译文自动评价方法利用深度神经网络进行融合。在WMT{'}19译文自动评价任务数据集上的实验结果表明,所提出的方法能够有效增强机器译文自动评价与人工评价的相关性。深入的实验分析进一步揭示了源语言句子信息在译文自动评价中发挥着重要的作用。"
}