We start with the baseline transformation to initialize the source and target embedding spaces and then our model learns an encoder based on morphological segments in the source side and their counterparts in the target space.
the transition matrix which is computed to produce a shared cross-lingual embedding space, is learned through morpheme representations and their composition in the source language.