Data Diversification: An Elegant Strategy For Neural Machine Translation
Table 4: Performances on low-resource translations. As done by flores, the from-English pairs are measured in tokenized BLEU, while to-English are measured in detokenized SacreBLEU.
['[BOLD] Method', '[BOLD] En-Ne', '[BOLD] Ne-En', '[BOLD] En-Si', '[BOLD] Si-En']
Specifically, the method achieves 5.7, 8.9, 2.2, and 8.2 BLEU for En-Ne, Ne-En, En-Si and Si-En tasks, respectively. In absolute terms, these are 1.4, 1.3, 2.2 and 1.5 BLEU improvements over the baseline model (flores). Without any monolingual data involved, our method establishes a new state of the art in all four low-resource tasks.