Attention Focusing for Neural Machine Translation by Bridging Source and Target Embeddings
Table 5: Ratios of over translation (ROT) on test sets. NN stands for nouns excluding proper nouns and temporal nouns, NR for proper nouns, DT for determiners, and CD for cardinal numbers.
['[BOLD] System', 'POS', '[BOLD] ROT(%)']
These data indicate that both systems have higher over translation with proper nouns (NR) and other nouns (NN) than with other POS tags, which is consistent with the results in Li et al. The likely reason is that these two POS tags usually have more unknown words, which are words that tend to be over translated. Importantly, these data also show that our direct bridging model alleviates the over translation issue by 15%, as ROT drops from 5.28% to 4.49%.