My View on the Reliability of MT
I feel that I owe some explanations after my first article about machine translation (MT). In my previous post, I stated that machine translation can be a very useful tool, but it cannot and should not replace the human translator. I will very briefly try to explain why, after which I promise to drop the topic for good :).
The first argument against machine translation (and I would include all engines here, not only Google and Bing) is creativity (or the lack thereof). Everyone agrees that humans are creative creatures, they can create stories, objects, works of arts, to name only a few. And believe it or not, language is probably the greatest creative achievement of the human mind. But not in the sense of a finite object, because language is not something ”made”, it’s something ”in the making” (an activity). This fact lies at the heart of Humboldt’s theory of language and is acknowledged by all modern paradigms of Linguistics. According to this principle every speech act is new even though it is indeed based on our historic linguistic experience. But the way in which we use our linguistic knowledge to create new meaning is completely different from the way a machine uses the corpora of text to ”create” new translations. Humans create new speech acts (in essence, a translation is a speech act) based on meaning and sense, they dress them up with words, which means that the same idea can be expressed in very many ways, using completely different words. A computer, on the other hand, will always use the same sentence to express a certain idea. And this brings us to the second part of my post.
The second argument against MT is meaning. Every translation course is based on the assumption that the students/trainees attending the course are fluent in at least two languages – their mother tongue and a source language. Clearly, in order for anyone to translate, they have to speak and understand the two languages. In other words, when they read and attempt to translate a text, they will be required to understand it. Not only do they have to make out the meaning of individual words, but also grasp the sense of the whole text. Mind you, it has been proven that the best approach to translation is a text-linguistic approach. So I am going to ask you the following question: Is a computer capable of grasping meaning? Can it understand a text? I’m afraid the answer to this question is no. A translation engine only recognizes words and sentences and uses a statistical model to compare them with parallel structures in the target language corpus in order to come up with the best solution. Wait a minute… Did I say it recognizes words? WRONG! It recognizes signifiers (signifiants) which are only graphic representations. It doesn’t even bother to go beyond signifiers and discover the actual meaning of these representations simply because it can’t! A computer does not speak any language. A computer does not understand meaning. A computer does not read texts, let alone understand them.
It’s true, MT has evolved a lot in the last couple of years and the statistic approach it uses is to a certain extent functional. But the question is, is this really enough? I mean if MT is so great, why does it need post editing? Why does it need human intervention? Yes, I know, some will argue that MT helps increase productivity. But is this all that matters? Does everything come down to money and quantity?…
Maybe a day will come when a computer will be able to fully understand us and yes, to translate flawlessly, but that day, my friends, will be the day computers will fully replace humans in all their activities…
