Volctrans Parallel Corpus Filtering System for WMT 2020
Runxin Xu, Zhuo Zhi, Jun Cao, Mingxuan Wang, Lei Li · 2020
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.xand 2.x/2.x for km-en and ps-en on From Scratch/Fine-Tune conditions.