Abstract
In this paper, we describe our submission to the Code-mixed Machine Translation (MixMT) shared task. In MixMT, the objective is to translate Hinglish to English and vice versa. For our submissions, we focused on code-mixed pre-training and multi-way fine-tuning. Our submissions achieved rank 4 in terms of automatic evaluation score. For Hinglish to English translation, our submission achieved rank 4 as well.- Anthology ID:
- 2022.wmt-1.111
- Volume:
- Proceedings of the Seventh Conference on Machine Translation (WMT)
- Month:
- December
- Year:
- 2022
- Address:
- Abu Dhabi, United Arab Emirates (Hybrid)
- Editors:
- Philipp Koehn, Loïc Barrault, Ondřej Bojar, Fethi Bougares, Rajen Chatterjee, Marta R. Costa-jussà, Christian Federmann, Mark Fishel, Alexander Fraser, Markus Freitag, Yvette Graham, Roman Grundkiewicz, Paco Guzman, Barry Haddow, Matthias Huck, Antonio Jimeno Yepes, Tom Kocmi, André Martins, Makoto Morishita, Christof Monz, Masaaki Nagata, Toshiaki Nakazawa, Matteo Negri, Aurélie Névéol, Mariana Neves, Martin Popel, Marco Turchi, Marcos Zampieri
- Venue:
- WMT
- SIG:
- SIGMT
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 1122–1125
- Language:
- URL:
- https://aclanthology.org/2022.wmt-1.111
- DOI:
- Cite (ACL):
- Raj Dabre. 2022. NICT at MixMT 2022: Synthetic Code-Mixed Pre-training and Multi-way Fine-tuning for Hinglish–English Translation. In Proceedings of the Seventh Conference on Machine Translation (WMT), pages 1122–1125, Abu Dhabi, United Arab Emirates (Hybrid). Association for Computational Linguistics.
- Cite (Informal):
- NICT at MixMT 2022: Synthetic Code-Mixed Pre-training and Multi-way Fine-tuning for Hinglish–English Translation (Dabre, WMT 2022)
- PDF:
- https://preview.aclanthology.org/emnlp-22-attachments/2022.wmt-1.111.pdf