Unsupervised Machine Translation Using Monolingual Corpora Only
Table 4: Ablation study on the Multi30k-Task1 dataset.
['[EMPTY]', 'en-fr', 'fr-en', 'de-en', 'en-de']
Ablation Study We perform an ablation study to understand the importance of the different components of our system. To this end, we have trained multiple versions of our model with some missing components: the discriminator, the cross-domain loss, the auto-encoding loss, etc. The most critical component is the unsupervised word alignment technique, either in the form of a back-translation dataset generated using word-by-word translation, or in the form of pretrained embeddings which enable to map sentences of different languages in the same latent space.