openalex_id:w2962801832
We participated in the WMT 2016 shared news translation task by building neural translation systems for four language pairs, each trained in both directions:English↔Czech, English↔German, English↔Romanian and English↔Russian.Our systems are based on an attentional encoder-decoder, using BPE subword segmentation for open-vocabulary translation with a fixed vocabulary.We experimented with using automatic back-translations of the monolingual News corpus as additional training data, pervasive dropout, and target-bidirectional models.All reported methods give substantial improvements, and we see improvements of 4.3-11.2BLEU over our baseline systems.In the human evaluation, our systems were the (tied) best constrained system for 7 out of 8 translation directions in which we participated. 12