Is Post-editing Dead?

by Han Mai
3 Minute Read

Many of us who have had the displeasure of post-editing a translation created by a machine would agree that the process is slow, tedious and out-of-style. However, there are always two sides of the story. So, we decided to ask our Twitter followers on their opinion of the post-editing process. The results? 47% of translators would rather go to the dentist than post-edit.

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While this may seem impressive, there’s still 33% who like to post-edit! So although post-editing may not be dead just yet, we can all be excited about advances in adaptive machine translation (MT) technology which create viable alternatives to an archaic process.

Some advocates of post-editing machine translation (PEMT) try making it sound like just another editing job; where the translator cleans up the MT output, much like an editor would do to the work of a human translator. Except that if you were editing the work of a colleague with as terrible translations as a machine has sometimes, you’d probably throw a muffin at their head. Not to mention, that your colleague would never learn that Jack London should not be translated to Jack Londres, no matter how many times you corrected them. Another muffin gone and wasted.

For trained linguists with the skills and abilities to pick up on nuances in language, culture and style, post-editing is dull and repetitive dirty work, and pays what you’d expect. Translator Lucy Pieper told us of the process of post-editing, “It doesn’t pay very well…and I spend so much time and effort cleaning it up.”

Of course, it’s not usually the decision of the translator to post-edit, but rather the client, who sees the benefits of using machine translation because it cuts down on cost. But post-editing machine translation opens you up to wonky-sounding translations with a higher margin for error. Not exactly good for business. Nonetheless, many companies are still choosing PEMT as a way to translate their content. Translator Dana Kruse laments this decision, “Customers think post-editing is super easy. Post-editing is a pain.”

Ms. Kruse uses Lilt for most of her translation work. On why she likes it, she said simply, “It works with me according to whatever I put in there.”

Indeed, interactive and adaptive MT systems like Lilt, work with the translator, instead of interfering with them. In 2016, Spence Green, the CEO at Lilt, wrote how “neither post-editing nor TM (Translation Memory) are the future of machine-assisted translation” in his article “Beyond Post-Editing: Advances in Interactive Translation Environments.” At the time, Lilt was still a young babe and the idea of an augmented translator, made more productive by machine assistance, sounded like a far-off science fiction fantasy. A human translator augmented (not replaced) by a machine, in order to work more efficiently and productively?

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Many of our early users were quick to see the advantage. “Tools like Lilt have changed my work as a translator in a number of ways. I’d say the three most important are the improvements in portability, speed, and creativity.” said Lizajoy Morales, a translator and early Lilt user.

We believe that the future of translation lies in human-centered translation. Adaptive MT systems put the translator at the center and assist them to translate better and faster without interfering with their work.

That means that translators can use the linguistic skills they’ve worked so hard to acquire and actually get compensated reasonably for it!

So what do you think of post-editing?

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Case Study: First Large-Scale Application of Auto-Adaptive MT

2 Minute Read

Combining Machine Translation (MT) with auto-adaptive Machine Learning (ML) enables a new paradigm of machine assistance. Such systems learn from the experience, intelligence and insights of their human users, improving productivity by working in partnership, making suggestions and improving accuracy over time. The net result is that human reviewers produce far higher volumes of content, with nearly the same level of quality, for a fraction of the time and cost. Machine assistance can save customers up to one half (or more) of the price of traditional high-quality human translation services. Or, if you’ve been used to machine translation alone and have been unhappy with the results, watch your translation quality rise dramatically with a marginal increase in price.

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The Augmented Translator: How Their Jobs are Changing and What They Think About It

3 Minute Read

Written by Kelly Messori The idea that robots are taking over human jobs is by no means a new one. Over the last century, the automation of tasks has done everything from making a farmer’s job easier with tractors to replacing the need for cashiers with self-serve kiosks. More recently, as machines are getting smarter, discussion has shifted to the topic of robots taking over more skilled positions, namely that of a translator. A simple search on the question-and-answer site Quora reveals dozens of inquiries on this very issue. While a recent survey shows that AI experts predict that robots will take over the task of translating languages by 2024. Everyone wants to know if they’ll be replaced by a machine and more importantly, when will that happen?

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