A Comparison of Transformer and Recurrent Neural Networks on Multilingual Neural Machine Translation
Table 5: Distribution of lexical, morphological, and reordering error types from the two MT approaches. Reported values are normalized with respect to the total error count of the respective bilingual reference model (NMT). ΔNMT are variations with respect to the bilingual reference models (NMT).
['Nl→De', '[BOLD] Recurrent NMT', '[BOLD] Recurrent M-NMT', '[BOLD] Recurrent Δ [ITALIC] NMT', '[BOLD] Recurrent ZST', '[BOLD] Recurrent Δ [ITALIC] NMT', '[BOLD] Transformer NMT', '[BOLD] Transformer M-NMT', '[BOLD] Transformer Δ [ITALIC] NMT', '[BOLD] Transformer ZST', '[BOLD] Transformer Δ [ITALIC] NMT']
We also report, for each error type and M-NMT and ZST system, the observed relative difference of errors with respect to the bilingual reference model (NMT).