Training on Synthetic NoiseImproves Robustness to Natural Noise in Machine Translation
Table 3: Ablation analysis for IWSLT 2016 de-en, with maximal natural noise in the test set. The top half displays experiments with only one type of noise, while the bottom half shows results with three out of four noise types.
['[BOLD] Training Noise', '[BOLD] BLEU', 'Δ']
We find that deletion is by far the most effective synthetic noise in preparing our model for natural orthographical errors, followed by insertion. The French and Czech datasets exhibit the same trend.