One of the most challenging issues for current state-ofthe-art word aligners is that they show poor generalization capability and are prone to errors when infrequent or unknown words (with respect to the training data) occur in new sentence pairs to be aligned (Farajian et al., 2014).
wA research would highly benefit from gold standard data specifically tailored to assess wA systems on this is-sue.