Improving Unsupervised Word-by-Word Translationwith Language Model and Denoising Autoencoder
Table 2: Translation results with different values of denoising parameters for German→English.
['[ITALIC] dper', '[ITALIC] pdel', '[ITALIC] Vins', 'Bleu [%]']
Firstly, for permutations, a significant improvement is achieved from dper=3, since a local reordering usually involves a sequence of 3 to 4 words. With dper>5, it shuffles too many consecutive words together, yielding no further improvement. This noise cannot handle long-range reordering, which is usually a swap of words that are far from each other, keeping the words in the middle as they are.