Code-Mixed text data consists of sentences having words or phrases from more than one language. Most multi-lingual communities worldwide communicate using multiple languages, with English usually one of them. Hinglish is a Code-Mixed text composed of Hindi and English but written in Roman script. This paper aims to determine the factors influencing the quality of Code-Mixed text data generated by the system. For the HinglishEval task, the proposed model uses multi-lingual BERT to find the similarity between synthetically generated and human-generated sentences to predict the quality of synthetically generated Hinglish sentences.
@article{arxiv.2206.08680,
title = {BITS Pilani at HinglishEval: Quality Evaluation for Code-Mixed Hinglish Text Using Transformers},
author = {Shaz Furniturewala and Vijay Kumari and Amulya Ratna Dash and Hriday Kedia and Yashvardhan Sharma},
journal= {arXiv preprint arXiv:2206.08680},
year = {2022}
}