For the successful set of Machine Translation Post-Editing Guidelines, a set of factors should be taken into account. In this document, expertise, content, CAT Tools, MT engines and types of Post-Editing are analyzed to measure their impact on the training of post-editors. The analysis of these factors is made through the use of polls and interactive discussions with the audience.
Below, you’ll find some statements regarding the current setting and some of the current research perspectives.
Machine translation post-editing is becoming commonplace. Professional translators are often faced with this unknown task with little training and support. Given the different processes involved during post-editing, research suggests that untrained translators do not necessarily make good post-editors.