Zero-Shot Dual Machine Translation
Table 2: BLEU score results for the experiments with four languages.
['[EMPTY]', '[BOLD] Phrase-based', '[BOLD] NMT-0', '[BOLD] NMT-F', '[BOLD] Dual-0']
Regarding the supervised translation directions, NMT-0 maintains the relative performance compared to the phrase-based results, that is, it is still 10-13 BLEU points lower, as in the previous experiment. However, the zero-shot directions which do not have Russian as the target language obtain a good performance comparing to the experiment with three languages. We do not have yet a good explanation for this phenomenon. Interestingly, the NMT base model performs much better also with Russian as the source language. While translating to Russian performs poorly. We can see that the performance is highly improved in this case as well. Moreover, it is consistent with what we saw in the previous experiment, i.e. the BLEU score that every zero-shot translation direction obtains is 2-3 BLEU points below of the supervised score of the base model.