Neural Machine Translation with Key-Value Memory-Augmented Attention
Table 4: Case-sensitive BLEU scores (%) on German⇔English translation task. “synthetic data” denotes additional 10M monolingual sentences, which is not used in this work.
['System', 'Architecture', 'De⇒En', 'En⇒De']
Our baseline achieves even higher BLEU scores to the state-of-the-art NMT systems of WMT17, which do not use additional synthetic data. Our proposed model consistently outperforms two strong baselines (i.e., standard and memory-augmented attention models) on both De⇒En and En⇒De translation tasks. These results demonstrate that our model works well across different language pairs.