@inproceedings{kriukova-etal-2025-ai,
    title = "{AI} for Interlinearization and {POS}-tagging: Teaching Linguists to Fish",
    author = "Kriukova, Olga  and
      Schmirler, Katherine  and
      Moeller, Sarah  and
      Lovick, Olga  and
      Genee, Inge  and
      Arppe, Antti  and
      Smith, Alexandra",
    editor = "Lachler, Jordan  and
      Agyapong, Godfred  and
      Arppe, Antti  and
      Moeller, Sarah  and
      Chaudhary, Aditi  and
      Rijhwani, Shruti  and
      Rosenblum, Daisy",
    booktitle = "Proceedings of the Eight Workshop on the Use of Computational Methods in the Study of Endangered Languages",
    month = mar,
    year = "2025",
    address = "Honolulu, Hawaii, USA",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/Ingest-2025-COMPUTEL/2025.computel-main.16/",
    pages = "139--149",
    ISBN = "None",
    abstract = {This paper describes the process and learn- ing outcomes of a three-day workshop on ma- chine learning basics for documentary linguists. During this workshop, two groups of linguists working with two Indigenous languages of North America, Blackfoot and D{\"e}n{\"e} Su ̨{\l}{\i}n{\'e}, became acquainted with machine learning prin- ciples, explored how machine learning can be used in data processing for under-resourced languages and then applied different machine learning methods for automatic morphologi- cal interlinearization and parts-of-speech tag- ging. As a result, participants discovered paths to greater collaboration between computer sci- ence and documentary linguistics and reflected on how linguists might be enabled to apply ma- chine learning with less dependence on experts.}
}