@inproceedings{dudy-bedrick-2018-compositional,
    title = "Compositional Language Modeling for Icon-Based Augmentative and Alternative Communication",
    author = "Dudy, Shiran  and
      Bedrick, Steven",
    editor = "Haffari, Reza  and
      Cherry, Colin  and
      Foster, George  and
      Khadivi, Shahram  and
      Salehi, Bahar",
    booktitle = "Proceedings of the Workshop on Deep Learning Approaches for Low-Resource {NLP}",
    month = jul,
    year = "2018",
    address = "Melbourne",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/ingest-emnlp/W18-3404/",
    doi = "10.18653/v1/W18-3404",
    pages = "25--32",
    abstract = "Icon-based communication systems are widely used in the field of Augmentative and Alternative Communication. Typically, icon-based systems have lagged behind word- and character-based systems in terms of predictive typing functionality, due to the challenges inherent to training icon-based language models. We propose a method for synthesizing training data for use in icon-based language models, and explore two different modeling strategies. We propose a method to generate language models for corpus-less symbol-set."
}