Abstract
We describe a project on introducing an in-house statistical machine translation system for marketing texts from the automobile industry with the final aim of replacing manual translation with post-editing, based on the translation system. The focus of the paper is the suitability of such texts for SMT; we present experiments in domain adaptation and decompounding that improve the baseline translation systems, the results of which are evaluated using automatic metrics as well as manual evaluation.
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