We describe our submission to the ITdomain translation task of WMT 2016. We perform domain adaptation with dictionary data on already trained MT systems with no further retraining. We apply our approach to two conceptually different systems developed within the QTLeap project: TectoMT and Moses, as well as Chimera, their combination. In all settings, our method improves the translation quality. Moreover, the basic variant of our approach is applicable to any MT system, including a black-box one.
['Rudolf Rosa', 'Roman Sudarikov', 'Michal Novák', 'Martin Popel', 'Ondrej Bojar']
Dictionary-based Domain Adaptation of MT Systems without Retraining