Unsupervised Neural Machine Translation with SMT as Posterior Regularization

14 Jan 2019Shuo RenZhirui ZhangShujie LiuMing ZhouShuai Ma

Without real bilingual corpus available, unsupervised Neural Machine Translation (NMT) typically requires pseudo parallel data generated with the back-translation method for the model training. However, due to weak supervision, the pseudo data inevitably contain noises and errors that will be accumulated and reinforced in the subsequent training process, leading to bad translation performance... (read more)

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Evaluation results from the paper


Task Dataset Model Metric name Metric value Global rank Compare
Unsupervised Machine Translation WMT2014 English-French SMT as posterior regularization BLEU 29.5 # 3
Unsupervised Machine Translation WMT2014 English-German SMT as posterior regularization BLEU 17.0 # 2
Unsupervised Machine Translation WMT2014 French-English SMT as posterior regularization BLEU 28.9 # 3
Unsupervised Machine Translation WMT2014 German-English SMT as posterior regularization BLEU 20.4 # 2
Unsupervised Machine Translation WMT2016 English-German SMT as posterior regularization BLEU 21.7 # 3
Unsupervised Machine Translation WMT2016 German-English SMT as posterior regularization BLEU 26.3 # 4