@inproceedings{yang-etal-2025-recontextualizing,
    title = {Recontextualizing Revitalization: A Mixed Media Approach to Reviving the N{\"u}shu Language},
    author = "Yang, Ivory  and
      Guo, Xiaobo  and
      Wang, Yuxin  and
      Zhang, Hefan  and
      Jia, Yaning  and
      Dinauer, William  and
      Vosoughi, Soroush",
    editor = "Christodoulopoulos, Christos  and
      Chakraborty, Tanmoy  and
      Rose, Carolyn  and
      Peng, Violet",
    booktitle = "Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing",
    month = nov,
    year = "2025",
    address = "Suzhou, China",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/ingest-emnlp/2025.emnlp-main.627/",
    pages = "12430--12439",
    ISBN = "979-8-89176-332-6",
    abstract = {N{\"u}shu is an endangered language from Jiangyong County, China, and the world{'}s only known writing system created and used exclusively by women. Recent Natural Language Processing (NLP) work has digitized small N{\"u}shu-Chinese corpora, but the script remains computationally inaccessible due to its handwritten, mixed-media form and dearth of multimodal resources. We address this gap with two novel datasets: N{\"u}shuVision, an image corpus of 500 rendered sentences in traditional vertical, right-to-left orthography, and N{\"u}shuStrokes, the first sequential handwriting recordings of all 397 Unicode N{\"u}shu characters by an expert calligrapher. Evaluating five state-of-the-art Chinese Optical Character Recognition (OCR) systems on N{\"u}shuVision shows that all fail entirely, each yielding a Character Error Rate (CER) of 1.0. Fine-tuning Microsoft{'}s TrOCR on N{\"u}shuVision lowers CER to 0.67, a modest yet meaningful improvement. These contributions establish the first multimodal foundation for N{\"u}shu revitalization and offer a culturally grounded framework for language preservation.}
}