Research
NLP
Facebook AI's WAT19 Myanmar-English Translation Task Submission
October 31, 2019
Abstract
This paper describes Facebook AI's submission to the WAT 2019 Myanmar-English translation task. Our baseline systems are BPE-based transformer models. We explore methods to leverage monolingual data to improve generalization, including self-training, back-translation and their combination. We further improve results by using noisy channel re-ranking and ensembling. We demonstrate that these techniques can significantly improve not only a system trained with additional monolingual data, but even the baseline system trained exclusively on the provided small parallel dataset. Our system ranks first in both directions according to human evaluation and BLEU, with a gain of over 8 BLEU points above the second best system.
AUTHORS
Written by
Peng-Jen Chen
Jiajun Shen
Vishrav Chaudhary
Ahmed El-Kishky
Guillaume Wenzek
Research Topics
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