Multi-Agent Cross-Translated Diversification for Unsupervised Machine Translation
Table 2: BLEU scores on the unsupervised IWSLT’13 English-French (En-Fr) and IWSLT’14 English-German (En-De) tasks with varying level k and diversification multiplier n.
['[BOLD] Method / Data', '[BOLD] En-Fr', '[BOLD] Fr-En', '[BOLD] En-De', '[BOLD] De-En']
As shown, 2nd level MACD with n=2 improves the performance in all four tasks by 2-3 BLEU compared to the baseline. Furthermore, increasing the multiplier to n=3 adds another 1 BLEU to the results. However, the experiments show that increasing it to n=4 does not improve the translation quality further. Furthermore, applying the 3rd level MACD seems to reduce the performance slightly, perhaps because the long daisy chain translation process induces more noises and deteriorates the sample quality. Thus, scaling up MACD’s synthetic parallel data may not always be beneficial, rather there is a saturation point that can be found through hyper-parameter tuning.