Back-Translation Sampling by Targeting Difficult Words in Neural Machine Translation
Table 3: German→English translation quality (Bleu).
['[EMPTY]', '[BOLD] Size', '[BOLD] 2014', '[BOLD] 2015', '[BOLD] 2016', '[BOLD] 2017']
As to be expected, re-training with additional parallel data yields higher performance than re-training with additional synthetic data. However, the differences between the Bleu scores of these two models are surprisingly small. This indicates that performing back-translation with a reasonably good reverse model already achieves results that are close to a system that uses additional manually translated data. This is inline with findings of \newcitesennrich-haddow-birch:2016: P16-11 who observed that the same monolingual data translated with three translation systems of different quality and used in re-training the translation model yields similar results.