Context Gates for Neural Machine Translation
Table 6: Correlation between context gate weight and improvement of translation performance. “Length” denotes the length of source sentence. “BLEU”, “Adequacy”, and “Fluency” denotes different metrics measuring the translation performance improvement of using context gates.
['[BOLD] Length', '[BOLD] BLEU', '[BOLD] Adequacy', '[BOLD] Fluency']
We confirm that context gate weight zi correlates well with translation performance. In other words, translations that contain higher zi (i.e., source context contributes more than target context) at many time steps are better in translation performance. We used the mean of the sequence z1,…,zi,…,zI as the gate weight of each sentence. We observed that context gate weight is positively correlated with translation performance improvement and that the correlation is higher on long sentences.