| dc.contributor.author |
Sharma, Yashvardhan |
|
| dc.date.accessioned |
2024-11-13T08:59:17Z |
|
| dc.date.available |
2024-11-13T08:59:17Z |
|
| dc.date.issued |
2022 |
|
| dc.identifier.uri |
https://aclanthology.org/2022.inlg-genchal.6/ |
|
| dc.identifier.uri |
http://dspace.bits-pilani.ac.in:8080/jspui/handle/123456789/16358 |
|
| dc.description.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. |
en_US |
| dc.language.iso |
en |
en_US |
| dc.publisher |
Association for Computational Linguistics |
en_US |
| dc.subject |
Computer Science |
en_US |
| dc.subject |
Code-Mixed text |
en_US |
| dc.subject |
HinglishEval task |
en_US |
| dc.subject |
BERT |
en_US |
| dc.title |
BITS Pilani at HinglishEval: Quality Evaluation for Code-Mixed Hinglish Text Using Transformers |
en_US |
| dc.type |
Article |
en_US |