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This paper describes our submission to the WMT20 sentence filtering task. Wecombine scores from (1) a custom LASER built for each source language, (2) aclassifier built to distinguish positive and negative pairs by semanticalignment, and (3) the original scores included in the task devkit. For themBART finetuning setup, provided by the organizers, our method shows 7% and 5%relative improvement over baseline, in sacreBLEU score on the test set forPashto and Khmer respectively.

Score Combination for Improved Parallel Corpus Filtering for Low Resource Conditions