@inproceedings{parikh-solorio-2021-normalization,
    title = "Normalization and Back-Transliteration for Code-Switched Data",
    author = "Parikh, Dwija  and
      Solorio, Thamar",
    editor = "Solorio, Thamar  and
      Chen, Shuguang  and
      Black, Alan W.  and
      Diab, Mona  and
      Sitaram, Sunayana  and
      Soto, Victor  and
      Yilmaz, Emre  and
      Srinivasan, Anirudh",
    booktitle = "Proceedings of the Fifth Workshop on Computational Approaches to Linguistic Code-Switching",
    month = jun,
    year = "2021",
    address = "Online",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/fix-sig-urls/2021.calcs-1.15/",
    doi = "10.18653/v1/2021.calcs-1.15",
    pages = "119--124",
    abstract = "Code-switching is an omnipresent phenomenon in multilingual communities all around the world but remains a challenge for NLP systems due to the lack of proper data and processing techniques. Hindi-English code-switched text on social media is often transliterated to the Roman script which prevents from utilizing monolingual resources available in the native Devanagari script. In this paper, we propose a method to normalize and back-transliterate code-switched Hindi-English text. In addition, we present a grapheme-to-phoneme (G2P) conversion technique for romanized Hindi data. We also release a dataset of script-corrected Hindi-English code-switched sentences labeled for the named entity recognition and part-of-speech tagging tasks to facilitate further research."
}