BITS Pilani at HinglishEval: Quality Evaluation for Code-Mixed Hinglish Text Using Transformers
Shaz Furniturewala, Vijay Kumari, Amulya Ratna Dash, Hriday Kedia, Yashvardhan Sharma
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.- Anthology ID:
- 2022.inlg-genchal.6
- Volume:
- Proceedings of the 15th International Conference on Natural Language Generation: Generation Challenges
- Month:
- July
- Year:
- 2022
- Address:
- Waterville, Maine, USA and virtual meeting
- Editors:
- Samira Shaikh, Thiago Ferreira, Amanda Stent
- Venue:
- INLG
- SIG:
- SIGGEN
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 35–38
- Language:
- URL:
- https://aclanthology.org/2022.inlg-genchal.6
- DOI:
- Cite (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.
- Cite (Informal):
- BITS Pilani at HinglishEval: Quality Evaluation for Code-Mixed Hinglish Text Using Transformers (Furniturewala et al., INLG 2022)
- PDF:
- https://preview.aclanthology.org/ingest-acl-2023-videos/2022.inlg-genchal.6.pdf