@inproceedings{lam-etal-2024-multi,
    title = "Multi-Tiered {C}antonese Word Segmentation",
    author = "Lam, Charles  and
      Lau, Chaak-ming  and
      Lee, Jackson L.",
    editor = "Calzolari, Nicoletta  and
      Kan, Min-Yen  and
      Hoste, Veronique  and
      Lenci, Alessandro  and
      Sakti, Sakriani  and
      Xue, Nianwen",
    booktitle = "Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)",
    month = may,
    year = "2024",
    address = "Torino, Italia",
    publisher = "ELRA and ICCL",
    url = "https://preview.aclanthology.org/fix-sig-urls/2024.lrec-main.1047/",
    pages = "11993--12002",
    abstract = "Word segmentation for Chinese text data is essential for compiling corpora and any other tasks where the notion of ``word'' is assumed, since Chinese orthography does not have conventional word boundaries as languages such as English do. A perennial issue, however, is that there is no consensus about the definition of ``word'' in Chinese, which makes word segmentation challenging. Recent work in Chinese word segmentation has begun to embrace the idea of multiple word segmentation possibilities. In a similar spirit, this paper focuses on Cantonese, another major Chinese variety. We propose a linguistically motivated, multi-tiered word segmentation system for Cantonese, and release a Cantonese corpus of 150,000 characters word-segmented by this proposal. Our work will be of interest to researchers whose work involves Cantonese corpus data."
}