What can we learn about the selection mechanism for post-editing?

Maja Popovic; Eleftherios Avramidis; Aljoscha Burchardt; David Vilar; Hans Uszkoreit

In: Proceedings of Workshop on Translation Post-Editing Technology and Practice. Machine Translation Summit (MT Summit-13), 13th, September 19-23, Xiamen, China, Proceedings of MT Summit XIV, 2013.


Post-editing is an increasingly common form of human-machine cooperation for translation. One possible support for the post-editing task is offering several machine outputs to a human translator from which then can choose the most suitable one. This paper investigates the selection process for such method to get a better insight into it so that it can be optimally automatised in future work. Experiments show that only about 70% of the selected sentences are the best ranked ones, and that selection mechanism is tightly related to edit distance. Furthermore, five types of performed edit operations are analysed: correcting word form, reordering, adding missing words, deleting extra words and correcting lexical choice.


finalSubmission.pdf (pdf, 53 KB )

Deutsches Forschungszentrum für Künstliche Intelligenz
German Research Center for Artificial Intelligence