An Empirical Comparison of Domain Adaptation Methods for Neural Machine Translation

In this paper, we propose a novel domain adaptation method named “mixed fine tuning” for neural machine translation (NMT). We combine two existing approaches namely fine tuning and multi domain NMT. We first train an NMT model on an out-of-domain parallel corpus, and then fine tune it on a parall…