Encoding Source Language with Convolutional Neural Network for Machine Translation
Table 2: BLEU-4 scores (%) of tagCNN model with dependency head words as additional tags (tagCNN_dep).
['[BOLD] Systems', '[BOLD] MT04', '[BOLD] MT05', '[BOLD] Average']
In this section, we study whether tagCNN can further benefit from encoding richer dependency structure in source language in the input. More specifically, the dependency head words can be used to further improve tagCNN model. For example, if xi is the embedding of an affiliated source word and xj the dependency head of word xi, the extended input of tagCNN would contain x(\textscAff,\textscnon−Head)i = [ x⊤i10]⊤ x(\textscnon−Aff,\textscHead)j = [x⊤j01]⊤ If the affiliated source word is the root of a sentence, we only append 0 as the second tagging bit since the root has no dependency head.