It is a universally acknowledged truth that Google has changed the world we live in, and one of their newer features, Google Translate, is also likely to have a big impact on the future of language and translation.
Traditionally, mechanical translation has relied on systematic matching of word meanings between languages, and reordering words based on different grammatical and structural rules. This literal methodology is faulty and full of pitfalls. The vocabularies and grammars of languages do not always line up in perfect or equivalent ways, which - though the linguistic diversity is beautiful - can make mechanical translation a frustrating process. According to an article in Slate, this is "the kind of process that translates kindergarten as children garden."
Google Translate's method, however, is very different from the traditional manner of "this equals that." According to Google, their translator surveys language patterns in a possibly endless variety of documents, books, and articles, and gives the reader an intelligent guess for how to best translate the language. This process is known as "statistical machine translation."
In Is That a Fish in Your Ear? David Bellos makes the point that Google Translate could not work without the countless human hours that have gone into translating the documents that are now available on the web. Essentially, as David Bellos sums it up, Google Translate relies on what has already been said in order to say something new; it simply reinvents the wheel of human activity. Though the software is recent, the process is timeless, akin to a baby cobbling together words for the first time after having listened to the way adults speak.
For more information about Google Translate and how they "teach" computers new languages, watch the video below.
This article was originally published in November 2011, and has been updated for the
October 2012 paperback release.
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