@inproceedings{toftrup-etal-2021-reproduction,
    title = "A reproduction of Apple`s bi-directional {LSTM} models for language identification in short strings",
    author = "Toftrup, Mads  and
      Asger S{\o}rensen, S{\o}ren  and
      Ciosici, Manuel R.  and
      Assent, Ira",
    editor = "Sorodoc, Ionut-Teodor  and
      Sushil, Madhumita  and
      Takmaz, Ece  and
      Agirre, Eneko",
    booktitle = "Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Student Research Workshop",
    month = apr,
    year = "2021",
    address = "Online",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/jlcl-multiple-ingestion/2021.eacl-srw.6/",
    doi = "10.18653/v1/2021.eacl-srw.6",
    pages = "36--42",
    abstract = "Language Identification is the task of identifying a document`s language. For applications like automatic spell checker selection, language identification must use very short strings such as text message fragments. In this work, we reproduce a language identification architecture that Apple briefly sketched in a blog post. We confirm the bi-LSTM model`s performance and find that it outperforms current open-source language identifiers. We further find that its language identification mistakes are due to confusion between related languages."
}