@inproceedings{han-etal-2022-automating,
    title = "Automating Interlingual Homograph Recognition with Parallel Sentences",
    author = "Han, Yi  and
      Sasano, Ryohei  and
      Takeda, Koichi",
    editor = "He, Yulan  and
      Ji, Heng  and
      Li, Sujian  and
      Liu, Yang  and
      Chang, Chua-Hui",
    booktitle = "Findings of the Association for Computational Linguistics: AACL-IJCNLP 2022",
    month = nov,
    year = "2022",
    address = "Online only",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/fix-sig-urls/2022.findings-aacl.20/",
    doi = "10.18653/v1/2022.findings-aacl.20",
    pages = "211--216",
    abstract = "Interlingual homographs are words that spell the same but possess different meanings across languages. Recognizing interlingual homographs from form-identical words generally needs linguistic knowledge and massive annotation work. In this paper, we propose an automatic interlingual homograph recognition method based on the cross-lingual word embedding similarity and co-occurrence of form-identical words in parallel sentences. We conduct experiments with various off-the-shelf language models coordinating with cross-lingual alignment operations and co-occurrence metrics on the Chinese-Japanese and English-Dutch language pairs. Experimental results demonstrate that our proposed method is able to make accurate and consistent predictions across languages."
}