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arXiv · 2010.14029

Volctrans Parallel Corpus Filtering System for WMT 2020

Runxin Xu·Zhuo Zhi·Jun Cao·Mingxuan Wang·Lei Li
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Abstract

In this paper, we describe our submissions to the WMT20 shared task on parallel corpus filtering and alignment for low-resource conditions. The task requires the participants to align potential parallel sentence pairs out of the given document pairs, and score them so that low-quality pairs can be filtered. Our system, Volctrans, is made of two modules, i.e., a mining module and a scoring module. Based on the word alignment model, the mining module adopts an iterative mining strategy to extract latent parallel sentences. In the scoring module, an XLM-based scorer provides scores, followed by reranking mechanisms and ensemble. Our submissions outperform the baseline by 3.x/2.x and 2.x/2.x for km-en and ps-en on From Scratch/Fine-Tune conditions, which is the highest among all submissions.

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Runxin Xu, Zhuo Zhi, Jun Cao, Mingxuan Wang, Lei Li. 2020-10-27. Volctrans Parallel Corpus Filtering System for WMT 2020. https://arxiv.org/abs/2010.14029

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