Back in July, we released a blog announcing a key milestone for SDL Machine Translation; we recorded that over 100 million words had been translated in SDL Trados Studio using our very own neural machine translation (NMT) since its release back in November 2019 - this was a very proud day for the SDL team indeed. Meanwhile, monthly average volumes have only increased and we now log over 100 million words being translated in Studio each month. Looking at these numbers, it is safe to say that adoption of SDL’s Machine Translation (MT) is on the rise, with no signs of slowing down.
This may come as no surprise to many; NMT is not just a phrase on everyone’s lips anymore, but is also something already being used by “the masses”. Just as translation memory (TM) technology fundamentally changed translation and led to a significant increase in productivity, NMT is now being accepted as another important new paradigm that leads to higher levels of productivity.
In recent years, the quality of machine translation has improved quite dramatically with Neural MT technology entering the scene - the effects of which have been felt across the whole of the supply chain. Language service providers (LSPs) and corporate organizations now have the option to translate larger volumes of content, plus they can afford to translate content that may have never been considered for translation before.
For the freelance translator, Post-Editing Machine Translation (PEMT) jobs have become more common, however their perceptions of using machine translation and accepting jobs such as these are still mixed. Whilst a good quality machine translation provider can aid a translator by increasing their productivity, we often hear that freelance translators are hesitant to utilize this technology, but why?
By Nicole loney