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Senior teacher, L. Lazukhina

Kostanai State University named after A. Baitursynov, Kazakhstan

CURRENT PROBLEMS OF MACHINE TRANSLATION

The advent of computers and information technologies has created a new electronic culture which replaced the print culture and the process of working with documents and information has been greatly simplified and sped. Machine translation programs and computer translation tools have become part of this new culture, so that this refers to a machine and automated translation. [4]

These concepts shouldn’t be confused. Very often, instead of "machine" it is used the word "automatic" and it does not affect the meaning. However, the term "automatic translation" has a very different meaning. Machine translation is the process of translating texts from one language to another using a special computer program, implemented by this program independently, albeit with subsequent editing of the translator. The automated translation programs simply help a person to translate the text. They are just tools – dictionaries, databases, glossaries facilitating and accelerating the traditional process of translation. Automation has the purpose of facilitating the work of the person, substituting of his hand forms and increasing productivity, while machine translation technology is used in order to minimize human involvement in the process, and ideally remove it from the process. [1] Yet still it is not achievable at this stage of technology development. So far there are no programs that are able to give completely adequate translation of foreign texts. Therefore, the problem of machine translation remains relevant at the moment.

         Modern technology has gone far ahead of the first attempts to "stick a translator into computer." FAMT- (Fully-Automated Machine Translation) and HAMT- (Human-Assisted Machine Translation) -systems are a footstep away from being called as artificial intelligence systems, as they already perform certain functions of the human brain: in particular, they design the text on the object data language based on the source one using the set of certain rules given in the form of structures and algorithms. There exist no absolutely universal algorithms, of course, for FAMT- and HAMT- nor even for MAHT (Machine-Assisted Human Translation) -systems, as different products are based on different approaches to translation. Nevertheless a general scheme can be made. It is worthy of note that this scheme is approximate, simplified, and within each procedure both human and machine carry out a range of different actions. A man enters the text into the computer and performs manual setting of SMT, i.e. defines the parameters of the source and object language, selects the base theme and terminological dictionaries for translating specialized vocabulary, sets limits for translating names appearing in the text, etc. The program searches for the word forms in the dictionary of the source language, and performs the morphological analysis of the input information. During the analysis other information may be obtained. The program searches for matches. First, it is made the translation of idioms, phraseological unities and stamps in this domain. Then they perform the definition of the basic grammatical characteristics of the remaining elements of the input text (e.g. nouns, verbs, tense, etc.). Usually at this stage monosemantic words are separated from the polysemantic ones, then the monosemantic words are translated according to the lists of equivalents, and for the translation of polysemantic words are used specialized dictionaries. Lexical analysis of the input information and the actual translation itself complete the procedure. At this stage people may get in the work of some programs to “prompt” the machine extra linguistic nuances that are not clear for it: e. g. which of the several meanings of the word should be chosen in this case.

Then the program performs a grammatical analysis of the resulting draft translation, in the course of which it is defined the missing grammatical information taking into account the data of the object language (for example, it is turned out, which of the three tenses of Russian verb in this context corresponds better to the "present continuous" tense of the English verb). It is performed the synthesis of output word forms and of the text as a whole. At this stage the work is done again by people who correct mistakes of the machine translation.

Thus, machine translation and computer-aided tools are instruments that can make the translation process more efficient, i.e. faster and less expensive.

But if computer tools really speed up the translation process, the efficiency of machine translation systems up to date is still questionable, despite the presence of advanced modern technologies. Therefore a translation done by a machine translation program, in any case cannot be regarded as a "finished product", it needs serious improvement. And despite the fact that the machines are made by people they cannot think like a man. Although the machine translation program provides the translated text, but errors in this text differ from the mistakes that people make. Besides, in this case, the approach to translation changes itself – the translator does not translate, but corrects mistakes, and mistakes are not human, these are mistakes of the machine. If we develop this idea, we can conclude that the work with a machine translation program does not need a translator, because a man who knows both these languages can do this work. [4] But it is difficult to agree to this point of view, because if a person owns at least one foreign language, he automatically owns some translation skills, therefore, is a translator in substance. Besides, it is doubtful that a person who has no linguistic knowledge could competently correct errors of the machine.

Therefore, in the training foreign languages one of the skills that students must master is the ability to perform the automatic translation of the text accompanying by his editing skills.

Literature:

1. Solovyov, A. V. Professional translation by computer. [Text] / A. Solovyov. – St. Petersburg.: Peter, 2008. – 160s.

2. Retsker, L. Translation theory and practice of translation. [Text]: Essays in linguistic theory of translation / L. Retsker. – M., Valent, 2004. – 244.

3. Machine translation [electronic resource] // URL: http://www.baidak.com/blog/machine-translation

4. All about machine translation [electronic resource] / / All about computers – URL: http://www.computerbild.ru