Automated/Machine translation – put to the test

We’re always being asked “why can’t I just use Google Translate/Babelfish/[insert name of machine translation tool here] instead? It’s free!” Where do I start?…

Well, it’s true of translation as much as of anything else: you do get what you pay for. So if you are paying nothing for your translation, you can guess how good (or not) it’s likely to be.

The free automated translation tools can sometimes be very useful for getting an understanding of the text. But if you intend on publishing the text, this is the last thing you would want to use as the automated translations are very literal.
For example, there’s nothing French about french fries, but a translation machine doesn’t know that and you could end up with a very odd text!

Machine or online translation tools are exactly that: a useful tool for trained linguists, or just to get a vague idea of what something is about, but are no substitute for human expertise and experience. A machine will not accurately translate anything more than the simplest phrases, and we’ve all seen the results when what comes out is totally wrong!
If you want to publish or use the text you are translating for any serious purpose, then steer well clear – don’t make your company or brand a laughing stock by cutting corners.
This is not a machine translation-bashing post, in fact I, like many linguists, am intrigued to see how this technology continues to develop, and use it frequently myself as one of several tools to help when I do need to use or understand something in a foreign language.

However, every tool has its correct and proper use – try using a hammer instead of a small screwdriver to repair your glasses, and you’ll soon see what I mean.

Machine translation is a really quick and handy way to decipher emails, websites you are browsing, and similar short snippets where your aim is to get a vague understanding. These tools work best at translating short standard or formulaic phrases, as these are things that can be taught to a machine in the form of rules.

Anything longer than a phrase or short sentence, and you will find that a translation machine will struggle to produce anything coherent.

We put machine translation to the test while working on improvements to our technology.

Currently, the Free and Light versions of we offer use automated/machine translation to translate incoming messages.

Here are the detailed results of our findings:

In the pdf comparison you can see red for wrong translated segments, yellow for mistranslations due to wrongly identifying the word order in English, and purple for things that shouldn’t have been translated (as they are company names, book titles…) or things that have not been translated and should’ve been.