Hovhannes Tamoyan


2020

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YerevaNN’s Systems for WMT20 Biomedical Translation Task: The Effect of Fixing Misaligned Sentence Pairs
Karen Hambardzumyan | Hovhannes Tamoyan | Hrant Khachatrian
Proceedings of the Fifth Conference on Machine Translation

This report describes YerevaNN’s neural machine translation systems and data processing pipelines developed for WMT20 biomedical translation task. We provide systems for English-Russian and English-German language pairs. For the English-Russian pair, our submissions achieve the best BLEU scores, with enru direction outperforming the other systems by a significant margin. We explain most of the improvements by our heavy data preprocessing pipeline which attempts to fix poorly aligned sentences in the parallel data.