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    <abstract>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 multilingual BERT to find the similarity between synthetically generated and human-generated sentences to predict the quality of synthetically generated Hinglish sentences.</abstract>
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%0 Conference Proceedings
%T BITS Pilani at HinglishEval: Quality Evaluation for Code-Mixed Hinglish Text Using Transformers
%A Furniturewala, Shaz
%A Kumari, Vijay
%A Dash, Amulya Ratna
%A Kedia, Hriday
%A Sharma, Yashvardhan
%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 furniturewala-etal-2022-bits
%X 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 multilingual BERT to find the similarity between synthetically generated and human-generated sentences to predict the quality of synthetically generated Hinglish sentences.
%U https://aclanthology.org/2022.inlg-genchal.6
%P 35-38

Markdown (Informal)

[BITS Pilani at HinglishEval: Quality Evaluation for Code-Mixed Hinglish Text Using Transformers](https://aclanthology.org/2022.inlg-genchal.6) (Furniturewala et al., INLG 2022)

• BITS Pilani at HinglishEval: Quality Evaluation for Code-Mixed Hinglish Text Using Transformers (Furniturewala et al., INLG 2022)

ACL

• Shaz Furniturewala, Vijay Kumari, Amulya Ratna Dash, Hriday Kedia, and Yashvardhan Sharma. 2022. BITS Pilani at HinglishEval: Quality Evaluation for Code-Mixed Hinglish Text Using Transformers. In Proceedings of the 15th International Conference on Natural Language Generation: Generation Challenges, pages 35–38, Waterville, Maine, USA and virtual meeting. Association for Computational Linguistics.