Can all languages be machine-translated?

AI-generated texts and machine translation are becoming more and more common. But can these technologies handle all languages? Basically, the more widely used a language is, the better the results will be. Machine-translation tools are more dependable for popular languages and frequent language pairs – think English, Spanish, French and German. That’s because there is a lot of data available in these languages to train the tools with. The technology tends to be less precise and dependable when translating from/into less common languages.

Questions to ask yourself when considering machine translation

  • Which tool will you be using? There are many different machine-translation services and models out there. Not all of them are equally capable, so your choice of tool will affect the quality of the translations you get out of it.
  • What is the text about? Machine translation tends to work well for general, everyday texts; it is less suited to translating complex or specialised texts.
  • Do you need specific terms to be used in the translation? Technological or sector-specific terms can be harder to machine-translate, irrespective of the language pair involved. When you work with Textforum, we can store your company-specific terms in a translation memory and termbase we’ve created just for you. That way, the result will sound exactly the way you want – even when it’s a machine translation.
  • To what extent does the target language differ from the original language? It’s harder to translate between languages that have a very different grammar or word order. Take English and Japanese: these languages use verbs and objects in the opposite order, which makes machine translation between the two trickier. The word order of English and Spanish, on the other hand, is much more similar, which tends to lead to better results.
  • Are there any homonyms in your text? Homonyms are words with the same spelling or pronunciation, but different meanings – like ‘bark’ (the sound a dog makes) and ‘bark’ (the hard outer covering of a tree). A machine-translation tool is not always able to tell which of the two meanings it should use.
  • Does the text contain lots of cultural nuances, informal expressions or perhaps even dialect? In that case, there’s a greater risk the machine-translation tool will misinterpret things. A human translator with excellent knowledge of the market and the text’s particular language variant would then be a better fit.

Develop a strategy for machine translation

Contact us if you’re wondering whether your texts could be machine translated. Together, we’ll assess the situation to find the most time- and cost-effective solution. Would 100% machine translation do the trick, or would it need to be combined with post-editing? Or would it be best for a professional translator to do the job after all?