hinglishNorm - A Corpus of Hindi-English Code Mixed Sentences for Text Normalization
Piyush Makhija, Ankit Kumar, Anuj Gupta
Abstract
We present hinglishNorm - a human annotated corpus of Hindi-English code-mixed sentences for text normalization task. Each sentence in the corpus is aligned to its corresponding human annotated normalized form. To the best of our knowledge, there is no corpus of Hindi-English code-mixed sentences for text normalization task that is publicly available. Our work is the first attempt in this direction. The corpus contains 13494 segments annotated for text normalization. Further, we present baseline normalization results on this corpus. We obtain a Word Error Rate (WER) of 15.55, BiLingual Evaluation Understudy (BLEU) score of 71.2, and Metric for Evaluation of Translation with Explicit ORdering (METEOR) score of 0.50.
BibTeX
@inproceedings{makhija-etal-2020-hinglishnorm,
title = "hinglish{N}orm - A Corpus of {H}indi-{E}nglish Code Mixed Sentences for Text Normalization",
author = "Makhija, Piyush and
Kumar, Ankit and
Gupta, Anuj",
editor = "Clifton, Ann and
Napoles, Courtney",
booktitle = "Proceedings of the 28th International Conference on Computational Linguistics: Industry Track",
month = dec,
year = "2020",
address = "Online",
publisher = "International Committee on Computational Linguistics",
url = "https://aclanthology.org/2020.coling-industry.13/",
doi = "10.18653/v1/2020.coling-industry.13",
pages = "136--145"
}