Study Shows Impact of Clean Data and Consolidation on Statistical Machine Translation Quality

New study into Automated Language Translation highlights need for clean and normalized data when sharing data. In cooperation with the Translation Automation User Society (TAUS), Asia Online conducted an experiment to determine the optimum approaches for building statistical machine translation (SMT) engines with shared data. The findings indicate that significant improvements in translation machine quality can be achieved with smaller pools of shared, clean data. (PRWeb Aug 26, 2009)

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