Unsupervised Statistical Machine Translation

EMNLP 2018 Mikel ArtetxeGorka LabakaEneko Agirre

While modern machine translation has relied on large parallel corpora, a recent line of work has managed to train Neural Machine Translation (NMT) systems from monolingual corpora only (Artetxe et al., 2018c; Lample et al., 2018). Despite the potential of this approach for low-resource settings, existing systems are far behind their supervised counterparts, limiting their practical interest... (read more)

PDF Abstract

Evaluation results from the paper


Task Dataset Model Metric name Metric value Global rank Compare
Machine Translation WMT2014 English-French SMT + iterative backtranslation (unsupervised) BLEU score 26.22 # 28
Machine Translation WMT2014 English-German SMT + iterative backtranslation (unsupervised) BLEU score 14.08 # 27
Machine Translation WMT2014 French-English SMT + iterative backtranslation (unsupervised) BLEU score 25.87 # 1
Unsupervised Machine Translation WMT2014 French-English SMT BLEU 25.9 # 6
Machine Translation WMT2014 German-English SMT + iterative backtranslation (unsupervised) BLEU score 17.43 # 3
Machine Translation WMT2016 English-German SMT + iterative backtranslation (unsupervised) BLEU score 18.23 # 5
Machine Translation WMT2016 German-English SMT + iterative backtranslation (unsupervised) BLEU score 23.05 # 3