Neural Machine Translation with External Phrase Memory
Table 1: Evaluation of translation quality, where we use boldface digits to denote the best performance.
['[BOLD] Models', '[BOLD] NIST02', '[BOLD] NIST03', '[BOLD] NIST04', '[BOLD] NIST05', '[BOLD] NIST06', '[BOLD] NIST08', '[BOLD] Ave.']
Clearly both the proposed phraseNetgate and phraseNetsoftmax significantly improves the translation quality in all cases. More specifically, On average, phraseNetgate yields about 3.45 BLEU score improvement over our baseline , phraseNetsoftmax yields about 2.13 BLEU score improvement over our baseline. Also, RNNsearch with expanded vocabulary (30K words) is 1.65 BLEU behind phraseNetgate. Surprisingly, phraseNetsoftmax comes behind phraseNetgate, despite its potential ability to take the content of the target phrase into the decision. We conjecture that this might be due to the difficulty in directly comparing the scores from two different types of scoring functions in the same pool of softmax.