Ottobre 18, 5 Reasons Not to Rely on Google Translate Many translators and other language service providers were shocked upon hearing the news that an American public institution has relied on Google Translate to evaluate immigrant applications.
ProPublica revealed some details about this practice. According to the publication, immigration officials in the U. The author of the article also cites an internal manual used to train officers who work for the federal agency charged with admitting immigrants.
So, if machine translation is good enough for the government, should companies also use it for their translations? Absolutely not! Google Translate is a free service provided by Google that translates words, phrases, and even entire texts in over languages. This machine translation service was introduced in Initially, Google used documents from the United Nations and the European Parliament to get the linguistic data necessary for creating its massive databases. Now, the software has been updated using AI and machine learning to improve the quality of translations.
The software analyses enormous amounts of data and, based on previous translations, tries to deliver accurate results. Most of the time, Google Translate is pretty accurate.
The pros and cons of Google translate not only impact professional translators in the language service industry, but rather anyone who chooses to use it as a translation tool. Certainly, online public access to a free, quick, and relatively accurate translation method represents significant progress in translation technology. But when one directly compares translation quality and accuracy using Google Translate with that of an experienced human translator, there is no real comparison.
The way that Google Translate works is that it uses frequency of word pairs between two languages as a database for its translations. Although this works well in some cases, often this means that it cannot put a translation into proper context without the help of a human.
In fact, it may in some circumstances come up with outright errors or extremely awkward literal translations. While these can often be amusing, there is nothing funny about making mistakes on serious business document translations or when critical information is communicated incorrectly. So what are the pros and cons of Google translate vs.
Let me demonstrate these issues more clearly by providing you with an example of a Google translation from Spanish into Greek and English for a common Spanish expression. Of course this is not a terribly damaging error, just cause for confusion. Recently, there was an incident involving the Malaysian Defense Ministry, who decided to use Google Translate to produce an English version of its official website. The English version of the website was soon taken down after several blatant mistakes went viral on Twitter and Facebook causing quite a bit of embarrassment.
So as you can see the pros and cons of google translate make it clear that, although you may sometimes have success using Google translate, you would not want to use it for anything of great importance without checking to make sure that there are no errors in context, grammar or otherwise. That is a job for a professional translator.
I will now proceed to decode. Pushkin need not shudder. Nonetheless, his view of translation as decoding became a credo that has long driven the field of machine translation.
In this scenario, human translators would become, within a few years, mere quality controllers and glitch fixers rather than producers of fresh new text.
Such a development would cause a soul-shattering upheaval in my mental life. Although I fully understand the fascination of trying to get machines to translate well, I am not in the least eager to see human translators replaced by inanimate machines.
Indeed, the idea frightens and revolts me. I learned that although the older version of Google Translate can handle a very large repertoire of languages, its new deep-learning incarnation at the time worked for just nine languages. Before showing my findings, though, I should point out that an ambiguity in the adjective deep is being exploited here. But does that sort of depth imply that whatever such a network does must be profound?
This is verbal spinmeistery. I am very wary of Google Translate, especially given all the hype surrounding it. It is accessible for free to anyone on Earth, and will convert text in any of roughly languages into text in any of the others. That is humbling.
To a mere pi-lingual, bai-lingualism is most impressive. Moreover, if I copy and paste a page of text in Language A into Google Translate, only moments will elapse before I get back a page filled with words in Language B. And this is happening all the time on screens all over the planet, in dozens of languages.
The practical utility of Google Translate and similar technologies is undeniable, and probably a good thing overall, but there is still something deeply lacking in the approach, which is conveyed by a single word: understanding. Machine translation has never focused on understanding language. Could an entity, human or machine, do high-quality translation without paying attention to what language is all about?
To shed some light on this question, I turn now to the experiments I did. I began my explorations very humbly, using the following short remark, which, in a human mind, evokes a clear scenario:. In their house, everything comes in pairs. Dans leur maison, tout vient en paires. The program fell into my trap, not realizing, as any human reader would, that I was describing a couple, stressing that for each item he had, she had a similar one.
Next I translated the challenge phrase into French myself, in a way that did preserve the intended meaning. Chez eux, ils ont tout en double. At home, they have everything in double. There is his own car and his own car, his own towels and his own towels, his own library and his own library. We humans know all sorts of things about couples, houses, personal possessions, pride, rivalry, jealousy, privacy, and many other intangibles that lead to such quirks as a married couple having towels embroidered his and hers.
But I still felt I should check the engine out more closely. After all, one swallow does not thirst quench. By the way, I checked my translation with two native speakers of German, including Karl Sigmund, so I think you can assume it is accurate. As for female scholars, well, they had no place in the system at all; nothing was clearer than that.
And scientists did not question anyway; There were few of them. So far, so good! But soon it grows wobbly, and the further down you go, the wobblier it gets. The last two sentences really bring out how crucial understanding is for translation.
The related letter noun Wissenschaftlerin , found in the closing sentence in its plural form Wissenschaftlerinnen , is a consequence of the gendered-ness of German nouns.
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