Neural Reranking Improves Subjective Quality of Machine Translation: NAIST at WAT2015
Table 2: A summary of the improvements and degradations caused by neural reranking.
['Type', 'Impr.', 'Degr.', '% Impr.']
From this figure, we can see that overall, neural reranking caused an improvement in 117 sentences, and a degradation in 33 sentences, corroborating the fact that the reranking process is giving consistent improvements in accuracy. Further breaking down the changes, we can see that improvements in word reordering are by far the most prominent, slightly less than three times the number of improvements in the next most common category. This demonstrates that the neural MT model is successfully capturing the overall structure of the sentence, and effectively disambiguating reorderings that could not be appropriately scored in the baseline model.