Secondly a 58% post-edit analysis may not require the same effort as a 58% fuzzy from a traditional Translation Memory because there is no information provided to help the translator see what needs to be changed in the first place. First of all you don’t know it was a 58% match until after the work was complete. I’m reliably informed that a better translation of this Machine Translated text would require a number of changes that would equate to a 58% fuzzy match:īut how would I know this, and is it correct to view the effort required here as a 58% fuzzy match and pay the translator on this basis? Well, if you could measure the effort in this way there are a few obvious things to consider. The first problem of course is that when you use Machine Translation you can’t see where the differences are between the suggested translation and the one you wish to provide.
So let’s table that right away because there are many ways to measure, and pay for, post-editing work and I’m not going to suggest a single answer to suit everyone.īut I think I can safely say that finding a way to measure, and pay for post-editing translations in a consistent way that provided good visibility into how many changes had been made, and allowed you to build a cost model you could be happy with, is something many companies and translators are still investigating. It would be very arrogant of me to suggest that I have the solution for measuring the effort that goes into post-editing translations, wherever they originated from, but in particular machine translation.
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