Comparing Translation and Post-editing: An Annotation Schema for Activity Units

Abstract

The current chapter introduces an annotation schema of TPR data that categorises post-editing behaviour into five different classes and compares general-language and domain-specific English-to-German translation and post-editing with respect to production times, key-logging (text production activity and text elimination activity) and eye-tracking data (total reading times on source text and on target text). The results support the hypothesis that post-editing is faster than translation from scratch for both domain-specific and non-domain-specific text types. When key-logging and eye-tracking data are taken into consideration, domain-specific texts require more effort when translating from scratch, but less effort, when the machine translation output is post-edited. It is hypothesized that the introduced annotation schema could provide more details about translation processes, and better insights into the differences between different domains.