Enigma variations4. Machines for tr

Enigma variations

4. Machines for translating from one language to another were first talked about in the 1930s. Nothing much happened, however, until 1940 when an American mathematician called Warren Weaver became intrigued with the way the British had used their pioneering Colossus computer to crack the military codes produced by Germany's Enigma encryption machines. In a memo to his employer, the Rockefeller Foundation, Weaver wrote: "I have a text in front of me which is written in Russian but I am going to pretend that it is really written in English and that it has been coded in some strange symbols. All I need to do is to strip off the code in order to retrieve the information contained in the text".

5. The earliest "translation engines" were all based on this direct, so- called "transformer", approach. Input sentences of the source language were transformed directly into output sentences of the target language, using a simple form of parsing. The parser did a rough/analysis of the source sentence, dividing it into subject, object, verb, etc. Source words were then replaced by target words selected from a dictionary, and their order rearranged so as to comply with the rules of the target language.

6. It sounds simple, but it wasn't. The problem with Weaver's approach was summarized succinctly by Yehoshua Bar-Hillel, a linguist and philosopher who wondered what kind of sense a machine would make of the sentence "The pen is in the box" (the writing instrument is in the container) and the sentence "The box is in the pen" (the container is in the [play] pen).

7. Humans resolve such ambiguities in one of two ways. Either they note the context of the preceding sentences or they infer the meaning in isolation by knowing certain rules about the real world - in this case, that boxes are bigger than pens (writing instruments) but smaller than pens (play-pens) and that bigger objects cannot fit inside smaller ones. The computers available to Weaver and his immediate successors could not possibly have managed that.

8. But modern computers, which have more processing power arid more memory, can. Their translation engines are able to adopt a less direct approach, using what is called "linguistic knowledge". It is this that has allowed Mr. Kamejima to produce e-j bank, and has also permitted NeocorTech of San Diego to come up with Tsunami and Typhoon - the first Japanese-language-translation software to run on the standard (English) version of Microsoft Windows.

9. Linguistic-knowledge translators have two sets of grammatical rule - one for the source language and one for the target. They also have a lot of information about the idiomatic differences between the languages, to stop them making silly mistakes.

10. The first set of grammatical rules is used by the parser to analyze an input sentence ("I read" The Economist "every week"). The sentence is resolved into a tree that describes the structural relationship between the sentence's components ("I" [subject], "read" (verb), "The Economist" (object) and "every week" [phrase modifying the verb]. Thus far, the process is like that of a Weaver-style transformer engine. But then things get more complex. Instead of working to a pre-arranged formula, a generator (i. е., a parser in reverse) is brought into play to create a sentence structure in the target language. It does so using a dictionary and a comparative grammar - a set of rules hat describes the difference between each sentence component in the source language and its counterpart in the target language. Thus a bridge to the second language is built on deep structural foundations.

11. Apart from being much more accurate, such linguistic- knowledge engines should, in theory, be reversible - you should be able to work backwards from the target language to the source language. In practice, there are a few catches which prevent this from happening as well as it might - but the architecture does at least make life easier for software designers trying to produce matching pairs of programs. Tsunami (English to Japanese) and Typhoon Japanese to English), for instance, share much of their underlying programming code.

12. Having been designed from the start for use on a personal computer rather than a powerful workstation or even a mainframe, Tsunami and Typhoon use memory extremely efficiently. As a result, they are blindingly fast on the latest PCs - translating either way at speeds of more than 300,000 words an hour. Do they produce perfect translations at the click of a mouse? Not by a long shot. But they do come up with surprisingly good first drafts for expert translators to get their teeth into.

One mistake that the early researchers made was to imagine that nothing less than flawless, fully automated machine translation would suffice. With more realistic expectations, machine translation is, at last, beginning to thrive.

Результаты (русский) 3:

Enigma вариации

4. Машин для перевода с одного языка на другой, в 1930-е гг.. Ничто не многое произошло, тем не менее, до 1940 года когда американский математик называется Уоррен Уивер стала интересует каким образом в Англии их новаторскую колосс компьютера на появление трещин в военных кодексов, Германия, Enigma шифрование машин. В заметку его работодателю,Фонд Рокфеллера, Уивер писал: "У меня есть текст в передней части me, которые записываются в русский, а я буду делать вид, что она действительно написаны на английском языке и что она была закодирована в некоторых странные символы. Все нужно делать в полоску кодекса с тем, чтобы получить информацию, содержащуюся в текст" .ветровому 5. В ближайшее время "перевод двигатели" основаны на этой прямой,