Post-editing is still a necessary step if machine translations are to be used
for more than just gisting. For efficiency and to avoid frustrations it is important
that the machine translation systems used in this application are able to adapt and
learn from previous errors.
We propose several techniques to learn from post-edits and present a planned
evaluation with human translators along with a custom user interface.