@inproceedings{zundi-avaajargal-2022-word,
    title = "Word-level Morpheme segmentation using Transformer neural network",
    author = "Zundi, Tsolmon  and
      Avaajargal, Chinbat",
    editor = "Nicolai, Garrett  and
      Chodroff, Eleanor",
    booktitle = "Proceedings of the 19th SIGMORPHON Workshop on Computational Research in Phonetics, Phonology, and Morphology",
    month = jul,
    year = "2022",
    address = "Seattle, Washington",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/jlcl-multiple-ingestion/2022.sigmorphon-1.15/",
    doi = "10.18653/v1/2022.sigmorphon-1.15",
    pages = "139--143",
    abstract = "This paper presents the submission of team NUM DI to the SIGMORPHON 2022 Task on Morpheme Segmentation Part 1, word-level morpheme segmentation. We explore the transformer neural network approach to the shared task. We develop monolingual models for world-level morpheme segmentation and focus on improving the model by using various training strategies to improve accuracy and generalization across languages."
}