Effective Parallel Corpus Mining using Bilingual Sentence Embeddings
Table 5: BLEU scores on WMT datasets of the NMT models trained on original UN pairs (Oracle) and on two versions of mined UN corpora.
['[EMPTY]', '[BOLD] en-fr', '[BOLD] en-es']
The models trained with mined pairs perform very close to the Oracle model, demonstrating the effectiveness of the proposed parallel corpus mining approach. Training on the mined sentence level pairs even does slightly better than using the Oracle data for en-es. This is presumably because the mined pairs are cleaner due to the filtering step. We notice, however, that training on the UN corpus gives translation results that are much lower than the state-of-the-art on the WMT evaluation sets. This is likely due to the fact that the UN parallel corpus is small and drawn from a particularly restricted domain.