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MACHINE TRANSLATION: PROFESSIONAL EXPERIENCE (on ground MT PARS and Polyglossum dictionaries, w. images)e-book, download


Bliehman

E-book, Word, 3.4 Mbyte, for download 340 Kbyte (in Englisch), 70pp, with images
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This brochure is a kind of introduction to an introduction to computer translation. It doesnt even have a list of references. It can hardly be looked upon as a thorough compendium like the well-known brilliant book by John Hutchins and Harold Somers. My task is much more modest. The fact is, I remember but well the way I felt when my teachers tried to introduce me to automatic text processing when I studied at Kharkov State University. They were very serious and professional, which scared me terribly! It would have been easier for them to address people of their level of knowledge, but a boy or a girl of eighteen or twenty needs something to begin with before mastering deep ideas and complicated terminology. I asked myself many times when listening to complicated introductory courses: If this is a mere introduction, will I ever be able to make head or tale of the post-introductory course?

EXAMPLE from Book: Translating 2.3.1. General principles: contemplation for those interested in details Now that I have shown you how the systems look and given you some substantial grammatical information, it would be interesting to see how they are used to translate texts. In other words, what translation philosophy is laid in the foundation of those systems? First I wanted to make use of the almost-classic definition of three translation approaches: direct, transfer-based, and interlingua-based. These terms look so very scientific that they have to be explained. Direct translation has the word-for-word basis. For example, when translating from Russian into English, the computer program substitutes each Russian word or phrase found in the dictionary with its English equivalent. This is called direct translation because the system is based on direct correspondence between 2 languages, such as Russian-English, German-Spanish, Dutch-French, etc. It can only translate between the given language pair, and its not capable of anallyzing the source language sentence for subsequent translation into another target language. On the contrary, the transfer approach presupposes independent analysis of the source text sentences as well as independent generation of the target text ones. This means that the system, instead of translating word-for-word, first analyzes the source sentence and comes up with a special grammatical representation of this sentence, which (representaton) is then transformed into a sentence in the target language. Transfer means the transition to the target language after the first stage of the translation process, the analysis. Generally speaking, the interlingua philosophy resembles the transfer one. You see, an interlingua is a special artificial language used for making source language sentence representations. The idea is really great! Just imagine that you have to develop an MT system to translate between 20 languages, which would make 400 language pairs! Which would be easier to make: 400 direct translation programs, or 20 programs for translating from each of the 20 languages into the interlingua plus 20 programs for translating from the interlingua into each of the 20? Well, the more I was thinking about all this, the more convinced I was became that it would hardly be possible to use this definition practically as it is very hard to draw a demarcation line between the above three approaches. Reason No 1 is that the champions of this definition consider what they call direct translation quite fruitless, while, on the other side, systems translating directly are sold and, what is more important, bought throughout the world, giving their developers honestly earned profits, the latter being sometimes rather high. Or maybe we have to admit that no pure direct translation systems really exist, and each system is a combination of philosophies, so a different kind of terminology should to be suggested. In each of our PARSes, the translation program first generates a word-for-word translation, and then brushes it up intensively, making it look as natural as it (the program) can. That's why I call our approach FTA - first-translate-then-analyze. Generally speaking, FTA is usually resorted to if system developers don't want to view the sentence as a single structural entity, considering it as a linear sequence of lexical units and regarding syntactic and semantic relations merely for disambiguation purposes. On the contrary, a system may first analyze the source text, and then translate it, using the results of this analysis, thus working according to the FAT - first-analyze-then-translate principle. Traditionally, the FAT-type systems consider the whole sentence as a syntactic (or even semantic-syntactic) unit, the basic idea being that the more information you use in your analysis, the better results you will obtain.


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