Statistical Modelling and Automatic Tagging of Human Translation Processes

Abstract

Advanced translation workbenches with detailed logging and eye-tracking capabilities greatly facilitate the recording of key strokes, mouse activity, or eye movement of translators and post-editors. The large-scale analysis of the resulting data logs, however, is still an open problem. In this chapter, we present and evaluate a statistical method to segment raw keylogging and eye-tracking data into distinct Human Translation Processes (HTPs), i.e., phases of specific human translation behavior, such as orientation, revision, or pause. We evaluate the performance of this automatic method against manual annotation by human experts with a background in Translation Process Research.