What you told us about translation productivity technology was also very interesting. Over 50% of respondents in our TTI research believe that innovations in translation software have yet to peak. The message is clear; you want more from your translation productivity tool!
With the upcoming release of SDL Trados Studio 2017, we have listened to the findings of this research and have two big new innovations at the core of Studio 2017 – upLIFT technology and AdaptiveMT.
So how can we enhance translation productivity technology with these innovations?
The most common daily scenarios for a translator can be a ‘No Match’ or ‘Fuzzy Match.’ We have looked at these two scenarios to come up with innovative upLIFT technology which addresses both.
upLIFT Fragment Recall – For the ‘No Match’ scenario
This is transformational new translation memory technology with matches coming directly from the TM by identifying matching fragments from existing translations.
upLIFT Fuzzy Match Repair – For the ‘Fuzzy Match’ scenario
SDL Trados Studio 2017 will get the most out of resources such as termbases and machine translation to repair your fuzzy matches. For example, if you translated “I have a white table" and you need to translate “I have a blue table", if you translated the word ‘BLUE’ before, Studio can automatically fix this sentence.
Is machine translation the next big translation productivity boost?
One surprise from our Translation Technology Insights research was despite there currently being a low level of machine translation adoption, it is set to rise over the next 5 years. What was also very revealing for us was 64% of respondents told us machine translation made them more efficient and 59% believe MT will be positive for the future.
If we take a look at standard machine translation, it is currently generated by the engine and is not updated with your post-edits, which can be frustrating and hinder productivity.
This is where our second big innovation comes in – AdaptiveMT.
SDL AdaptiveMT is a self-learning machine translation engine providing a personalized MT output for you. The self-learning happens in real time with no extra effort required and means you never have to post-edit the same correction over and over again. This will free up more time for your translations, making you much more productive.
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The Translation Technology Insights research has helped us shape and develop the future of SDL Trados Studio, starting with the upcoming release of SDL Trados Studio 2017. I hope you are as excited as we are about the future of translation productivity technology!