NTT’s Neural Machine Translation Systems for WMT 2018
Makoto Morishita, Jun Suzuki, Masaaki Nagata · 2018
This paper describes NTT's neural machine translation systems submitted to the WMT 2018 English-German and German-English news translation tasks.Our submission has three main components: the Transformer model, corpus cleaning, and right-to-left nbest re-ranking techniques.Through our experiments, we identified two keys for improving accuracy: filtering noisy training sentences and right-to-left re-ranking.We also found that the Transformer model requires more training data than the RNN-based model, and the RNN-based model sometimes achieves better accuracy than the Transformer model when the corpus is small.