Neural Machine Translation with Supervised Attention
Table 3: BLEU comparison for large scale translation task. The development set is nist02, and the test sets are nist05,nist06 and nist08. ‘*’ denotes that SA-NMT is significantly better than Moses, NMT1 and NMT2 with p<0.01. Note that Moses is trained with more bilingual sentences and an additional monolingual corpus.
['Systems', 'nist02', 'nist05', 'nist06', 'nist08']
We find that both standard NMT generally outperforms Moses except NMT1 on nist05. The proposed SA-NMT achieves significant and consistent improvements over all three baseline systems, and it obtains the averaged gains of 2.2 BLEU points on test sets over its direct baseline NMT2. It is clear from these results that our supervised attention mechanism is highly effective in practice.