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O. A. Kyrychenko,
Y. V. Kalashnyk, PR-84
Different electronic devices have become common nowadays. Due to the fundamental research in the systems of algorithms and in the establishment of lexical equivalence in different strata of lexicon, machine translation has made considerable progress in recent years.
But nevertheless there is a problem: machine cannot correctly translate all grammatical phenomena and presently there is no such translator which could replace the person.
Machine translation is an autonomous operating system with strategies and approaches that can be classified as follows:
The direct strategy, the first to be used in machine translation systems, involves a minimum of linguistic theory. This approach is based on a predefined source language-target language binomial in which each word of the source language syntagm is directly linked to a corresponding unit in the target language with a unidirectional correlation, for example from English to Spanish but not the other way round.
The transfer strategy focuses on the concept of "level of representation" and involves three stages. The analysis stage describes the source document linguistically and uses a source language dictionary. The transfer stage transforms the results of the analysis stage and establishes the linguistic and structural equivalents between the two languages. It uses a bilingual dictionary from source language to target language. The generation stage produces a document in the target language on the basis of the linguistic data of the source language by means of a target language dictionary.
The pivot language strategy is based on the idea of creating a representation of the text independent of any particular language. This representation functions as a neutral, universal central axis that is distinct from both the source language and the target language. In theory this method reduces the machine translation process to only two stages: analysis and generation. The analysis of the source text leads to a conceptual representation, the diverse components of which are matched by the generation module to their equivalents in the target language. The research on this strategy is related to artificial intelligence and the representation of knowledge. The systems based on the idea of a pivot language do not aim at direct translation, but rather reformulate the source text from the essential information. At the present time the transfer and pivot language strategies are generating the most research in the field of machine translation. With regard to the pivot language strategy, it is worth mentioning the Dutch DLT (Distributed Language Translation) project which ran from 1985 to 1990 and which used Esperanto as a pivot language in the translation of 12 European languages.
It should be repeated that unless the systems function within a rigidly defined sphere, as is the case with TAUM-MЙTЙO, machine translation in no way offers a finished product. As Christian Boitet, director of GETA (Grenoble) says in an interview given to the journal Le franзais dans le monde Nє314 in which he summarizes the most important aspects of MT, it allows translators to concentrate on producing a high-quality target text. Perhaps then "machine translation" is not an appropriate term, since the machine only completes the first stage of the process. It would be more accurate to talk of a tool that aids the translation process, rather than an independent translation system.
Apart from this function of providing a rough idea of what a given text contains and its utility when deciding whether not this would be worth translating, MT is only efficient where applied to texts with an appropriate degree of standardisation and coherency. In short, a text that can be translated by a computer must be written in a way that the computer can understand: there must be no ambiguity, and it must contain only terms contained in the computer's dictionary and which always have the same meaning.
This type of controlled language - which imposes major constraints on writers - has few areas of use beyond that of particular types of technical documentation that are sufficiently voluminous to justify the investment.
The best-known, and perhaps the most efficient of all MT systems is used in Canada for translating weather forecasts from English into French and vice-versa. These are created from a highly limited, self-contained unit of standard phrases.
Otherwise, MT is mainly used for a pre-translation phase that must be followed by intensive revision process in order to make the target text suitable for publication.
The extremely high costs of setting up and managing parameters for MT software and its dictionaries are a major obstacle when automatic translation.
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