Sep 04, 2012

Computer Assisted Translation – The Right Tool for the Job?

written by Keith Blasing

As we argued elsewhere, (  the latest statistical machine translators, like Google Translate, reach their limits quickly unless you already know both languages. So what about computer assisted translation (CAT) tools that are designed to boost productivity for translators who do already know both languages? Do they do what they claim to do? Are there hidden disadvantages? Is there any decrease in quality in exchange for the increase in productivity?

Yes, yes, and yes.

Most CAT tools work by drawing on a “translation memory” (TM) to automatically insert known translations for certain words, phrases, or sentences (“translation units” or TUs) that are stored in the TM. Obviously this saves the translator time that would otherwise be spent typing the words and, if necessary, looking them up in a dictionary. If you have a well-stocked TM and a text with a lot of repetition, you can have a significant portion of it translated with the push of a button. Your job as the translator is then to go fill in the remainder and make sure it all fits together. Sounds great. So what could possibly go wrong? Well, a few things…

The polysemy problem: words and phrases don’t always mean the same thing, or have the same translation, in different contexts. If your TM has the term “adversary action” from a legal context, it won’t give you the right translation for that phrase in a security context. For this reason, CAT tools tend to work best if the translator only operates in one particular field, or if the translator or translation agency maintains different TMs for different fields. And this takes time, which is what the CAT tool was designed to save in the first place.

The garbage-in-garbage-out problem: as with any machine translation, everything in a CAT tool’s TM ultimately comes from something produced by a human translator, and if the human makes a mistake, as humans do, that mistake will be replicated until the TM is corrected. TMs must be regularly updated and corrected. And this takes time, which is what the CAT tool was designed to save in the first place.

The syntax problem: differences between languages are not just in the terminology. Word order and other grammatical differences are also important. When people write (or translate), they tend to think in full clauses, not in smaller lexical units. A CAT tool can insert whole sentences and even paragraphs, but exact matches that long don’t happen terribly often. If you are translating without a CAT tool inserting words and phrases for you, you tend to read a whole clause in the original and quickly reformulate the whole clause in the target language. If you have used a CAT tool to insert individual words and phrases, you often end up having to go back and reformulate the whole clause where the word or phrase was inserted (if you don’t do this, the sentence will just sound clunky, if it makes sense at all). And this takes time, which is what the CAT tool was designed to save in the first place.

There are other issues as well, including the learning curve associated with using a CAT tool really well, the cost of buying and updating it, and problems with compatibility between different types of CAT software. But, on the other hand, if you were translating this article and you had a TM containing a good translation of the sentence “And this takes time, which is what the CAT tool was designed to save in the first place,” then you would have a 72-word head start. That’s not a complete game-changer, but it is a little bit of a boost.

In the final analysis, if you use a CAT tool well under the right circumstances, it can save a little time. Probably not so much time that it will ever radically change the expectations for how much a translator can produce in a day. But for some translators and translation companies that have realistic expectations and a plan for how to use a CAT tool effectively, it might be the right choice. 

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