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2022 EMNLP EMNLP 2022

NICT at MixMT 2022: Synthetic Code-Mixed Pre-training and Multi-way Fine-tuning for Hinglish–English Translation

Abstract

AbstractIn 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.

🌉 Interdisciplinary Bridge — Deep Learning and Machine Learning and Natural Language Processing
🧭 Keyword Pioneer — multi-way fine-tuning
🐝 Cross-Pollinator — Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Robotics, Security & Privacy, Speech & Audio

Authors

Raj Dabre

Topics

Natural Language Processing > Applications > Machine Translation Machine Learning > Learning Types > Transfer Learning Deep Learning > Learning Types > Fine-Tuning

Keywords

machine translation synthetic datum code-mixed translation multi-way fine-tuning hinglish english translation
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