@inproceedings{xiang-etal-2024-cantonese,
    title = "{C}antonese Natural Language Processing in the Transformers Era",
    author = "Xiang, Rong  and
      Liao, Ming  and
      Li, Jing",
    editor = "Wong, Kam-Fai  and
      Zhang, Min  and
      Xu, Ruifeng  and
      Li, Jing  and
      Wei, Zhongyu  and
      Gui, Lin  and
      Liang, Bin  and
      Zhao, Runcong",
    booktitle = "Proceedings of the 10th SIGHAN Workshop on Chinese Language Processing (SIGHAN-10)",
    month = aug,
    year = "2024",
    address = "Bangkok, Thailand",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/jlcl-multiple-ingestion/2024.sighan-1.8/",
    pages = "69--79",
    abstract = "Despite being spoken by a large population of speakers worldwide, Cantonese is under-resourced in terms of the data scale and diversity compared to other major languages. This limitation has excluded it from the current {\textquotedblleft}pre-training and fine-tuning{\textquotedblright} paradigm that is dominated by Transformer architectures.In this paper, we provide a comprehensive review on the existing resources and methodologies for Cantonese Natural Language Processing, covering the recent progress in language understanding, text generation and development of language models.We finally discuss two aspects of the Cantonese language that could make it potentially challenging even for state-of-the-art architectures: \textit{colloquialism} and \textit{multilinguality}."
}