Sulis: An Open Source Transfer Decoder for Deep Syntactic Statistical Machine Translation

We evaluated the productivity increase of statistical MT post-editing as compared to traditional translation in a two-day test involving twelve participants translating from English to French, Italian, German, and Spanish. The test setup followed an empirical methodology. A random subset of the entire new content produced in our company during a given year was translated with statistical MT engines trained on data from the previous year. The translation environment recorded translation and post-editing times for each sentence. The results show a productivity increase for each participant, with significant variance across inviduals.