Abstract
We present our submission to the WMT19 Robustness Task. Our baseline system is the CUNI Transformer system trained for the WMT18 shared task on News Translation.
Quantitative results show that the CUNI Transformer system is already far more robust to noisy input than the LSTM-based baseline provided by the task organizers. We further improved the performance of our model by fine-tuning on the in-domain noisy data.