@inproceedings{sorokin-2019-convolutional,
    title = "Convolutional neural networks for low-resource morpheme segmentation: baseline or state-of-the-art?",
    author = "Sorokin, Alexey",
    editor = "Nicolai, Garrett  and
      Cotterell, Ryan",
    booktitle = "Proceedings of the 16th Workshop on Computational Research in Phonetics, Phonology, and Morphology",
    month = aug,
    year = "2019",
    address = "Florence, Italy",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/iwcs-25-ingestion/W19-4218/",
    doi = "10.18653/v1/W19-4218",
    pages = "154--159",
    abstract = "We apply convolutional neural networks to the task of shallow morpheme segmentation using low-resource datasets for 5 different languages. We show that both in fully supervised and semi-supervised settings our model beats previous state-of-the-art approaches. We argue that convolutional neural networks reflect local nature of morpheme segmentation better than other semi-supervised approaches."
}