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Extracting Pre-ordering Rules from Chunk-based Dependency Trees for Japanese-to-English Translation
2011
Machine Translation Summit
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The processing of many natural languages suffers from scarce linguistic resources. We introduce the idea of compatibility to extend training data for machine translation: If translation hypotheses by multiple systems are measured as compatible, they are considered as reliable predictions. By this way, we generate virtual parallel data per bridge language, and re-compiling on this corpus improves our machine translation quality by more than 30% relatively.
dblp:conf/mtsummit/WuSDTN11
fatcat:5jdzevjqdvaxfibtg6mk7g3qty