Abstract

Machine translation systems, when they are used in a commercial context for publishing purposes, are usually used in combination with human post-editing. But human post-editing often becomes a bottleneck in the whole MT workflow. Thus understanding the process of human post-editing is crucial in order to maximise the benefit of machine translation systems. This study observes professional Japanese post-editors’ work and examines the effect of the amount of editing made during post-editing, source text characteristics, and post-editing actions, on the post-editing speed. The results indicate that a number of factors, such as sentence structure, sentence function types, use of product specific terms, and post-editing patterns and behaviour, have effect on the post-editing speed in an intertwined manner.