One Sunday, at one of our weekly salsa sessions, my friend Frank brought along a Danish guest. I knew Frank spoke Danish well, since his mother was Danish, and he, as a child, had lived in Denmark. As for his friend, her English was fluent, as is standard for Scandinavians. Frank would write a message in English, then run it through Google Translate to produce a new text in Danish; conversely, she would write a message in Danish, then let Google Translate anglicize it.
How odd! My own experiences with machine-translation software had always led me to be highly skeptical about it.
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But my skepticism was clearly not shared by these two. Indeed, many thoughtful people are quite enamored of translation programs, finding little to criticize in them.
This baffles me. When I first got interested in the subject, in the mids, I ran across a letter written in by the mathematician Warren Weaver, an early machine-translation advocate, to Norbert Wiener, a key figure in cybernetics, in which Weaver made this curious claim, today quite famous:. 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.
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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. 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 pilingual, bailingualism 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. 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 made.
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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. But I still felt I should check the engine out more closely. After all, one swallow does not thirst quench. It describes a group of idealistic Viennese intellectuals in the s and s, who had a major impact on philosophy and science during the rest of the century. 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.
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The last two sentences really bring out how crucial understanding is for translation. Aside from that blunder, the rest of the final sentence is a disaster.
Take its first half. It just consists of English words haphazardly triggered by the German words. The translation engine was not imagining large or small amounts or numbers of things. It was just throwing symbols around, without any notion that they might symbolize something. For decades, sophisticated people—even some artificial-intelligence researchers—have fallen for the Eliza effect.
Google Translate is all about bypassing or circumventing the act of understanding language. It denotes a profoundly human art form that graciously carries clear ideas in Language A into clear ideas in Language B, and the bridging act not only should maintain clarity, but also should give a sense for the flavor, quirks, and idiosyncrasies of the writing style of the original author. Whenever I translate, I first read the original text carefully and internalize the ideas as clearly as I can, letting them slosh back and forth in my mind.
Needless to say, most of this halo is unconscious. Translate offline camera, voice and text free: English-Spanish translator gratis. Spanish-English offline dict.
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