PEPr: Post-Edit Propagation Using Phrase-based Statistical Machine Translation.
Michel G. Simard, George Foster · 2013
Translators who work by post-editing ma-chine translation output often find them-selves repeatedly correcting the same er-rors. We propose a method for Post-edit Propagation (PEPr), which learns post-editor corrections and applies them on-the-fly to further MT output. Our proposal is based on a phrase-based SMT system, used in an automatic post-editing (APE) setting with online learning. Simulated experi-ments on a variety of data sets show that for documents with high levels of internal repetition, the proposed mechanism could substantially reduce the post-editing effort. 1