It’s pretty much twenty years I’ve been in this industry, from when I first started a degree in translation, naively thinking I would and could be a professional translator, to spending the best part of the past ten years doing production management, business and IT development and training.

In that time, machine translation (MT) has gone from:

“Not there” to

“Yeah right, ha ha, never going to happen” to

“Oh, this client’s doing it, but it’s pretty awful” to

“Maybe we should consider doing it?” to

“Doing it, and it’s not that bad” to

“Actually, it’s just another productivity tool”.

These days, we see a lot of MT at STP. Our excellent Technology team develop and maintain a host of MT engines for our internal use. We get MT output from clients and end-clients, and it ranges in quality and type from pure Google Translate to highly customised account-specific engines. What has been interesting is that companies have almost exclusively wanted a product which is full human quality.

If you ask me, the bottom line with MT is that when it’s used correctly, it allows us to translate more content faster, and within the same budget than before MT. And that’s great, it means that our target languages aren’t particularly threatened by English, as companies continue to see the value in producing content in their customers’ native tongues. For someone with a degree in Finnish translation, that’s a nice thought – there are only 5.5 million of us Finns after all!

What has become abundantly clear in the past few years of STP ramping up our use and development of MT is that our linguists’ MT post-editing skills are at the core of our ability to produce that full human quality. And that requires training.

This spring, we were certified to ISO 18587 on machine translation post-editing. This is a new ISO standard that has been developed to address the requirements for post-editing skills and training, rather than the technical development or implementation of MT engines. It’s not a particularly onerous standard to meet, provided that you are running a legitimate operation.

What the standard does do, though, is put the onus on the language service provider (LSP) to provide appropriate, robust training which ensures that the linguists working on MT output know how MT works, how post-editing is different to editing translation memory matches, how to give feedback and improve the engines efficiently, and how post-editing is best approached. And I think that’s the least we owe our translators.

And what being certified to the standard does is that it tells not only the outside world but also our clients and translators that we as a company know what we’re doing with MTPE. It tells them that our linguists are trained and know what they’re doing with MTPE, and that, essentially, it’s safe to trust your MT in our hands – what comes out the other end is another great STP translation.

I am sometimes a bit jealous of our translators who have made my old dream a reality, especially when it comes to figuring out how to use technology in the translation process. That said, I realised a long time ago that I would have at best been a mediocre translator, so I’m glad I found my calling on the business side of things. I certainly wouldn’t want to move to another industry, that’s for sure!

Raisa McNab is STP’s Learning and Development Manager and the ATC’s Lead on Standards. She holds an MA in Translation from the University of Turku in Finland.

This article first appeared in the June 2018 edition of STP’s Icebreaker newsletter.

Icebreaker June 2018, Machine Translation, Productivity, Translation Technology