One question I often hear when telling people I’m a translator is:“Can’t computers do that now?” I find this question surprising, as it exhibits a disturbing lack of awareness for what a translator actually does. Although it may not be all too surprising to hear this perception voiced by someone who has never learned a foreign language, even those with a grasp of the difficulties that pervade language translation often contend that the hurdles are merely technical, and that sooner or later machine translation will reach maturity. Indeed, if a computer program can beat Kasparov at chess, why can’t we develop one to master the task of translation?
Google seems to think it can, and has been touting the positive results of its statistic-based approach to machine translation. Whereas previous attempts to write translation programs involved efforts by linguists to define rules for transcribing text from one language to another, Google has thrown its weight behind a different approach in which reams of text are fed into a computer for the development of probability based models. Although advances have been made with this approach, and computers are likely to close the gap on human translators in coming years, it seems doubtful that a computer will ever surmount all of the hurdles facing machine translation. An interesting article in The Atlantic highlights some of the basic problems faced by machine translation, such as variance in word order and grammatical structure between languages. Far more problematic for development of an accurate and reliable translation program, however, are the idiomatic and cultural properties of language.
The panacea of intercultural exchange envisioned by some is complicated by the fact that computers don’t understand that institutional and cultural environments often inform specific texts. Translation is an act of negotiation, and sometimes suitable equivalents for certain expressions or terms do not exist. Oftentimes, the translator must heavily modify the target text to arrive at an appropriate adaptation. Take the following sentence, for example: “Die Gebaeude im Bezirk sind zu über 80 Prozent von gründerzeitlicher Altbausubstanz geprägt.” The real problem here, of course, is the word gründerzeitlich, a term that has no equivalent in English. (Google’s translation software doesn’t event attempt to deal with it, yielding “The buildings in the district are more than 80 percent from gründerzeitliche houses marked substance.”)
German readers know that the Gründerzeit was an historical period that generated a specific architectural style in Germany and Austria. English-speaking readers lack this context. An effective translation of the above sentence would take this realization into account and perhaps offer a gloss. Here’s what I came up with: “Over 80% of the buildings in the district were originally constructed in the German architectural period known as the Gründerzeit (“founding epoch”).
This doesn’t seem all that complicated on the face of it, but it requires a certain sensitivity to intercultural contexts, something that a computer program running on probability models lacks. There is literally no way to arrive at the formulation “originally constructed inthe architectural period” without an act of interpretation and awareness for one’s reader.