NLIP_Lab-IITH Low-Resource MT System for WMT24 Indic MT Shared Task

• URL: http://arxiv.org/abs/2410.03215v1
• Date: Fri, 4 Oct 2024 08:02:43 GMT
• Title: NLIP_Lab-IITH Low-Resource MT System for WMT24 Indic MT Shared Task
• Authors: Pramit Sahoo, Maharaj Brahma, Maunendra Sankar Desarkar,
• Abstract summary: We describe our system for the WMT 24 shared task of Low-Resource Indic Language Translation. Our primary system is based on language-specific finetuning on a pre-trained model. We achieve chrF2 scores of 50.6, 42.3, 54.9, and 66.3 on the official public test set for eng$rightarrow$as, eng$rightarrow$kha, eng$rightarrow$lus, eng$rightarrow$mni respectively.
• Score: 9.476463361600826
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: In this paper, we describe our system for the WMT 24 shared task of Low-Resource Indic Language Translation. We consider eng $\leftrightarrow$ {as, kha, lus, mni} as participating language pairs. In this shared task, we explore the finetuning of a pre-trained model motivated by the pre-trained objective of aligning embeddings closer by alignment augmentation \cite{lin-etal-2020-pre} for 22 scheduled Indian languages. Our primary system is based on language-specific finetuning on a pre-trained model. We achieve chrF2 scores of 50.6, 42.3, 54.9, and 66.3 on the official public test set for eng$\rightarrow$as, eng$\rightarrow$kha, eng$\rightarrow$lus, eng$\rightarrow$mni respectively. We also explore multilingual training with/without language grouping and layer-freezing. Our code, models, and generated translations are available here: https://github.com/pramitsahoo/WMT2024-LRILT.

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