Avoid the frustrating and time-consuming process of correcting the same machine translation errors time and time again with our break-through AdaptiveMT engines. These engines self-learn from your post-edits so that MT output is unique to your style, content and terminology. Now you can trust your own personal MT engine to form part of your translation DNA!
Experience the speed of the latest innovation in machine translation (MT). AdaptiveMT continuously learns and improves in real time as users post-edit, delivering MT output unique to your style, content and terminology.
How does it work?
Before the postedit, the engine has some opinion about how to translate the respective phrase.
When the postedit comes in, the adaptive technology will learn the new translation.
When the same phrase comes up again, there is a competition between the engine's original translation and the newly learned translation. Who wins that competition depends on various statistical factors; it's not always the new translation.
However, if the old translation wins, and the posteditor produces the new translation again, the adaptive technology will learn it again; thus, the third time around, the new translation has a much bigger chance of winning over the old one.
AdaptiveMT is machine translation that starts of as a basis by using SDL Language Cloud which you have today. So it doesn't matter what other resources you have as this works independently of those.
All you would do is correct the machine translation and then two things would happen when you confirm it:
1. The corrected TU would be sent to your Translation Memory as normal
2. The machine translation engine would take note of your correction so it offered the corrected translation next time
Now, you may well ask why this is useful given you already have this in your TM now? The reason it's useful is because the correction would be applied to other similar segments that are not translated yet but would benefit from the correction you have made. The machine translation will start to adapt to the way you are translating with improved translations for segments that you do not find in your TM.
So your TM/Termbases/Dictionaries have nothing to do with this. It's not the same as training an Engine with thousands or TUs that you have translated in the past. This is much more dynamic.