by Chris Durand
Machine translation is the use of software to translate text from one language to another, usually without assistance from a human translator. It is a fascinating field that is changing rapidly, but here’s my take on where things stand today.
Machine translation is cheap, and it is getting better every day. I was encouraged by the success of IBM’s Jeopardy-playing system Watson in drubbing its human challengers. Watson’s ability to “understand” idioms and natural language will contribute greatly to the future of machine translation.
Translation projects vary in requirements for accuracy as shown in the following diagram. For projects jobs where accuracy is less important, machine translation is a workable alternative. An example of this would be a company support forum, with huge amounts of user-supplied content. It is not cost-effective to pay a human translator to translate every post by a user into numerous languages. However, a machine translation engine that has been tuned to translate support issues for a particular product won’t create perfect results, but may still be a valuable resource to users. And creating value is what translation is all about.
Of course there are many translation jobs where accuracy is critical, such as legal documents. And translations of literature, poetry, and the like will remain difficult for machine translation software for years since there is much more to this sort of translation than accuracy, such as style and other artistic considerations.
But with continuing advances in computing and linguistics, the line shown in the above diagram will move steadily to the right over time.
Given the high variability of machine translation results (read: really bad translation), human translators still must review the results, reducing the cost advantage of machine translation. Some customers try to save money by running their material though a generic translation service like Google Translate and taking the results to human translators to “clean up”. Don’t bother. It’s usually cheaper to just let skilled translators do the job from scratch if you want a good translation.
Bad translations create a number of problems, such as damaging your brand and resulting in unhappy users. Would you buy a blender from a company if the box had a bunch of obvious translation mistakes on it? If they don’t care enough to get a professional translation done for their product, what does that say about the company’s commitment to quality?
And remember that paragraph or link text on your website that you forgot to get translated? You know, the one you just ran through Google Translate and are about to post to your website hoping no one will notice? Don’t. Can you identify an obvious error in Chinese? Or Arabic? Which brings us to…
It’s not hard to imagine catastrophic outcomes from bad machine translation, but here are two humorous examples:
- From the Department of Not Recognizing Machine Translation Errors, we have the “Translation Server Error” café in China. This is legendary in translation circles. Apparently the owners of the café were thoughtful enough to translate their restaurant name from Chinese to English. Unfortunately, the online translation server they used was not working properly, and they printed up a bright, new sign with the English name “Translation Server Error”. (Though they probably got far more publicity out of their failed translation than if a professional translator had done the job correctly, so perhaps this is not a gaffe at all.)
Years ago my father-in-law was taking a French class and had to write a short introduction of himself to the class (in French). To check his work, he pasted his French about how his grandson Hans lives in Portland into an online translation site to check his work, and got back the following:
Our only grandson, Grunts, also lives has Portland.
We still call my nephew Grunts to this day.