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Improving transfer-based MT systems with automatic refinements

In this paper, we describe an Automatic Rule Refiner that, given online post-editing information, traces errors back to problematic translation rules and proposes concrete fixes to such rules. Evaluation results on an English-to-Spanish Transfer-based MT system show that this approach generalizes beyond sentences corrected by bilingual speakers to unseen data. We show that by applying automatic refinements, higher translation accuracy can be achieved as measured by automatic evaluation metrics.