@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://aclanthology.org/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}.",
}
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%0 Conference Proceedings
%T HinglishEval Generation Challenge on Quality Estimation of Synthetic Code-Mixed Text: Overview and Results
%A Srivastava, Vivek
%A Singh, Mayank
%Y Shaikh, Samira
%Y Ferreira, Thiago
%Y Stent, Amanda
%S Proceedings of the 15th International Conference on Natural Language Generation: Generation Challenges
%D 2022
%8 July
%I Association for Computational Linguistics
%C Waterville, Maine, USA and virtual meeting
%F srivastava-singh-2022-hinglisheval
%X 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 https://codalab.lisn.upsaclay.fr/competitions/1688.
%U https://aclanthology.org/2022.inlg-genchal.3
%P 19-25
Markdown (Informal)
[HinglishEval Generation Challenge on Quality Estimation of Synthetic Code-Mixed Text: Overview and Results](https://aclanthology.org/2022.inlg-genchal.3) (Srivastava & Singh, INLG 2022)
ACL