There are probably quite a few translation and localization managers out there, who often have to fend off that “idea” to use machine translation. Colleagues or managers look at the likes of Google Translate and they look at the time and money spent on creating human-made translations – and suddenly machine translation seems like a fantastic option.
Translation guy has a few insights on this in his recent blog post. As usual, the post is well written, insightful and does not shy away from critique. There are many other examples of machine translation gone wrong, such as the infamous “translate server error“.
In essence, there are four use cases at present where machine translation does add value:
- so-called “gisting”, i.e. if you want to quickly and roughly understand what a text in a certain language says;
- pseudo-localization, i.e. testing a piece of software with regards to internationlisation or localisability.
- translation of content that wouldn’t otherwise get translated: this is a grey one, though. It certainly doesn’t apply to highly visible or printed content. You might want to use MT on support cases or forum posts, but they should be clearly labeled as having been translated using MT.
If someone thinks that you should use MT for anything else, simply provide them with a few examples, back-translations etc. This will quickly change their minds. Or refer them to the comment to this post which is a back-translation from this post translated into German and then English again using google translate.