Cseq2seq: Cyclic Sequence-to-Sequence Learning
Table 2: AER scores of word alignments deduced by different neural systems. The lower the score, the better the alignment quality.
['[BOLD] System', '[BOLD] AER']
Secondly, we treated the update gate as word alignments, and evaluated its quality in terms of alignment error rate (AER) following Tu et al. Tu et al. Consistent with the translation results, Cseq2seq-I with last-state strategy achieves the best alignment score. Notice that Cseq2seq does not aim at inducing high-quality word alignments. Instead, these AER results yielded by Cseq2seq demonstrate that the GRU gates inside Cseq2seq indeed learns what should be translated during translation.