@inproceedings{srivastava-singh-2022-hinglisheval,
    title = "{H}inglish{E}val Generation Challenge on Quality Estimation of Synthetic Code-Mixed Text: Overview and Results",
    author = "Srivastava, Vivek  and
      Singh, Mayank",
    editor = "Shaikh, Samira  and
      Ferreira, Thiago  and
      Stent, Amanda",
    booktitle = "Proceedings of the 15th International Conference on Natural Language Generation: Generation Challenges",
    month = jul,
    year = "2022",
    address = "Waterville, Maine, USA and virtual meeting",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/fix-sig-urls/2022.inlg-genchal.3/",
    pages = "19--25",
    abstract = "We hosted a shared task to investigate the factors influencing the quality of the code- mixed text generation systems. The teams experimented with two systems that gener- ate synthetic code-mixed Hinglish sentences. They also experimented with human ratings that evaluate the generation quality of the two systems. The first-of-its-kind, proposed sub- tasks, (i) quality rating prediction and (ii) an- notators' disagreement prediction of the syn- thetic Hinglish dataset made the shared task quite popular among the multilingual research community. A total of 46 participants com- prising 23 teams from 18 institutions reg- istered for this shared task. The detailed description of the task and the leaderboard is available at \url{https://codalab.lisn.upsaclay.fr/competitions/1688}."
}