Do you remember when you got your last smartphone? Or your last PC?

After unpacking/unwrapping it, you probably started to configure it, and as part of this process you maybe changed its language.

Worldwide, we are used to electronic appliances that speak our own language: Simplified Chinese, Japanese, Russian, Italian, Czech — you can change it as easily as pressing a button.

But how are these translations done?

Translating the user interfaces of electronic appliances is not an easy task if you want to get it right. It’s not just a matter of translating, but of taking into account the available space in case you need to abbreviate or look for shorter synonyms, the context (in which menu will this string appear?), and the real meaning of the string. Developers tend to use a rather particular language when defining the messages for your phone or printer, for example, which are always easy to understand when they appear in a simple text file.

When you take all this into account and come up with a translation that makes sense, that’s localization.

Localization is translation-plus: it takes into account various different variables (context, length, culture) to find the right words.

All these parameters have to be borne in mind when translating user interface menus; however, they are also important when translating web pages, newsletters, emails for customers — the more context and information the translator gets from the client, the better will the localization reflect the real aim of the original message.

Machine Translation

Once upon a time we all thought it would be impossible for humans to fly, or to talk with someone miles away, or to travel to the moon. All this has changed thanks to technology.

We also thought machines wouldn’t be able to translate text usefully, and it’s now long ago that we used to see those funny examples of literal translation, such as “Made in Turkey” translated as “Hecho en Pavo”.

Nowadays, there are still plenty of funny examples; however, most of the automatic translation engines have evolved, and the results have improved a lot.

In cases such as documentation, with short sentences consisting of unambiguous instructions, automatic translation can be useful, as long as the translation is edited afterwards. It can certainly help to save time and money.

However, there are cases in which automatic translation doesn’t yet make sense. Marketing texts with double meanings, texts that show some kind of feelings or sarcasm, where it is difficult to grasp the real intention of the writer, are still a challenge for automatic translation. In these cases, the editor would probably have to spend too much time trying to figure out the meaning of the translation, going back to the original text and changing the final result.

Technology should keep on helping us to get coherent and good translations; however, to make sure the final result is correct, a final check from a human translator will always be needed.

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