Using Automatic Machine Translation Metrics to Analyze the Impact of Source Reformulations.

This paper investigates the usefulness of automatic machine translation metrics when analyzing the impact of source reformulations on the quality of machine-translated user generated content. We propose a novel framework to quickly identify rewriting rules which improve or degrade the quality of MT output, by trying to rely on automatic metrics rather than human judgments. We find that this approach allows us to quickly identify overlapping rules between two language pairs (English- French and English-German) and specific cases where the rules’ precision could be improved.