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1)The study of the history of the origin, formation and development of terminological field "nanocomputer technologies" in the Russian language;

2)Description of word-formation types, operating in the nanocomputer sublanguage;

3)Identifying features of word-formation processes of nanocomputer sublanguage in the modern Russian language;

4).Analysis of the process of borrowing terms, identifying trends of internationalization of nanocomputer sublanguage's lexicon.

The main methods of this work are the experimental and statistical methods, method of semantic, quantitative and quality analysis.

A.V. Superanskaya points out that "in the analysis of terms should be treated as lexical and conceptual fields. For terms they are fundamental. Without this extralinguistic grounds it is impossible to build the terminological field" [5, p. 112]. The set of terms of nanocomputer technologies forms a terminological field. The terminological field "is a kind of area of existence of term, within it has all its characteristic signs, the area artificially delineated and specially guarded from foreign intrusion" [5, p. 110]. Terminological issues and many other critical issues constitute today the list of current nanocomputer research and development.

Currently, the computer terminology is entering its fifth period of development, which, in our opinion, is characterized by a rapid growth of interest in nanotechnology. M. A. Levin argues that "the science of computers over the last 20 years have not only moved far ahead, but evolved, and therefore changed its terminology" [6, p. 147]. The list of terms with the prefix nano- is constantly supplemented and regularly updated, for example, nanoelectronic system, nanostructure, nanocomputer, programmed nanoparticle, nanotransistor, nanoprocessor.

These lexical units can be considered, as terms and preterms. O. B. Ivanov stressed that "Russian nanotechnological terminology is at the initial stage of formation, as evidenced by the large number of preterms" [7,p. 8].

Because currently, there are no dictionaries of nanocomputer terms, the research material

for this article is based on the terms of our R u s s i a n v e r s i o n o f F r e n c h - A r a b i c e l e c t r o n i c d i c t i o n a r y , "the torch – ساربن ", which includes the most common terms in computer science and computer engineering (2000 terms) (available at: https://www.esi.dz/index.php/english/3034-2016-09-25-08-25-32) and "Dictionary of nanotechnology and nanotechnology-related terms" (589 terms) (available at: http://thesaurus.rusnano.com/).

The analysis of 2589 computer and nanotechnology terms shows that nanocomputer terms are 74 term. This number is 2.85 % of the total quantity of computer and nanotechnology terms.

It's hard to disagree with the linguistic point of view, according to which, terminological field must contain three main zones: the core, the central part and periphery. The set of nanocompuetr terms is an emerging system that is based on the achievements of nanotechnology in the field of computer technology. This terminological field consists of a core constituting the terms of the actual computer technology that reflects the specifics of nanotechnology and related technologies, for example, molecular assembler, nanites, intelligent molecules. The number of such terms is 36 nanocomputer terminological units (48,64 % of the total). The periphery of the field of this terminology includes borrowed terms from related disciplines, for example, nanodiagnostics, DNA computer, nanotransistor. The number of such terms is 14 nanocomputer terminological units (of 18.91 % of the total). The central part of the nanocomputer field is formed by the rest of terms, that belongs to the nanotechnology sublanguage or computer sub-

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language for example, integrated circuits, nanostructure, single-electron transistor. The total volume of these terms was 24 nanocomputer lexical units (32,43 % of total).

Table 2

Nanocomputer terminological field

In the formation of the nanocomputer sublanguage terms two main sources are involved, which can be roughly described as external and internal. The external source represented by the units included in the nanocomputer sublanguage terminology from other languages and other scientific fields, the internal source is represented by units, formed in the Russian language with the participation of its private diversion. The external source is represented by calques and borrowings and certain part of terminoelements of general language of science. Here are some examples of scientific terminoelements in nanocomputer terminology: calculation, method, system.

In this study, we propose the following classification of methods of forming the nanocomputer sublanguage terms:

A)Borrowing, which refers to the verbal occurrences from other languages, as well as calque;

B)Syntactic method, in which terminological phrases or compound terms are formed;

C)Morphological-syntactic method, which are compounding, conversion and abbrevia-

tions;

D)The morphological method, which includes affixation;

E)Semantic ways, which includes terminologization, the expansion and contraction of values, the metaphorization and metonymization.

In the analyzed material terms-calques are well represented, among which the first place belongs to the semantic calques of English terms for example, intelligent molecules →

интеллектуальные молекулы, molecular computer → молекулярный компьютер, smart composites → умные композиты. The number of such terms is 52 nanocomputer terminological units (70.27 % of the total).

Table 3

Nanocomputer terms-calques

When working with the nanocomputer sublanguage terms, it was revealed that the main external source of these terms is a cross-language and a cross-disciplinary borrowing from the English language, for example, nanites → наниты, nanorobot → наноробот, assembler → ассемблер, nanochip → наночип, qubit → кубит. Borrowing terms is a consequence of the influence of English on the Russian language in the field of terminology of nanocomputer technologies. The number of borrowed terms is 22 nanocomputer terminological units (29.73 % of the total).

Table 4

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Nanocomputer borrowed terms

The term system of computer technologies and nanotechnologies of the English language is the main source for all other languages. This is due to two factors: first, the US is the forerunner in these industries, major developments belong to this country; secondly, the international language of scientific publications and technical documentation is English, which is also the dominant language of international communication, providing a cross-language and crosscultural communication. The formation of terminology system computer technology and nanotechnology began primarily in the English language.

Development of information technologies and nanotechnologies is closely connected with other sciences: physics, biology, microelectronics, chemistry, mechanics, medicine, etc. This is because the borrowed terms from these areas are widely represented in the analyzed material of nanocomputer sublanguage, for example

f r o m p h y s i c s : quantum computer,

f r o m b i o l o g y : biomolecular code, DNA computer, Edelman bio-computer,

f r o m m i c r o e l e c t r o n i c s : nanotransistor, nanosensor, nanochip,

f r o m c h e m i s t r y : smart composites, smart molecules, synthetic molecules,

f r o m m e c h a n i c s : nanocar, molecular nanomachine,

f r o m m e d i c i n e : neurocomputing, nanodiagnostics, etc.

They are an integral part of the studied terminology. Intersystem borrowing can be explained by the interdisciplinary of computer technology and nanotechnology. However, the terms borrowed from related disciplines, when used in the field of computer technology and nanotechnology do not change their lexical meaning, while remaining, in essence, terms of original fields.

Despite the fact that nanocomputer technology are not sufficiently developed yet, the discoveries are already being applied in practice. The study showed that computer terms have the closest connection with nanotechnology terms. Interdisciplinary connections between computer science and nanotechnology are close enough. Thus, as an interdisciplinary area, nanocomputer technologies involve the terminology of many scientific disciplines, including nanotechnology and Informatics.

Special complex concepts in nanocomputer technologies contribute to use phrases of various types. One of the most productive ways of formation of nanocomputer terms is the syntactic way, i.e. the use of phrases to denote a scientific concept.

The number of components in the nanocomputer collocations varies from two to six. The study showed the presence of a sufficiently large number of two component terms-phrases, for example, smart materials, nanoelectromechanical systems. The number of binary terminological word combination is 31 nanocomputer terminological units (41,89 % of the total). It is expected that multicomponent terms with the development of this sublanguage will be abbreviations.

Table 5

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Nanocomputer binary terminological word combinations

It is known that the main types of morphological-syntactic method are compounding, conversion and abbreviations. The nanocomputer sublanguage analysis showed that nanocomputer terms formed by compounding or by conversion are not found. Number of termsabbreviations is the smallest percentage of the total number of terms in this sublanguage. Nanocomputer terms-abbreviations are only 03: artificial intelligence (AI), molecular modeling (MM), Nanotube-Based/Nonvolatile Random Access Memory (NRAM) (4.05 % of the total). It is interesting to note that terms-abbreviations were found in the hybrid terms specific to computer technology and nanotechnology, for example, DNA computer, DNA microchip.

Table 6

Nanocomputer terms-abbreviations

Most of the international terminoelements involved in the formation of terminological units using the method of addition. According to V. P. Danilenko, the main characteristic feature of such terminoelements lies in the commonality of their values and tightness of the parts of the addition for the classification ranks items [8, p. 126].

The most common type of formation of nanocomputer terms is the morphological method of word formation. The designation of the concepts in nanocomputer terminology is often formed prefixed way by attaching the prefix nano - to the already existing lexical unit. The prefix “nano” means one billionth of any value. It understands most of those who use the words with this prefix. These terms are often extended its original meaning in the new system without retaining their sound and graphic form. Here the meaning of terms is almost the same.

An important source for the formation of terms in the Russian language is verbal units that have been created using Greco-Latin, or international, terminoelements, whose values are known to the scientists of one specialty and understandable to researchers who are carriers of a variety of languages. Features such terms are semantic availability, accuracy, brevity and ease of formation [9, p. 162].

Note that researchers in the field of nanotechnology, convinced that it is not enough to add the prefix nano - to existing technical terms, for example, the term nanocomputer, we can change the prefix nano - in the super - to the existing nanotechnological term, for example, supercomputer, etc. Terms from this area can easily attach to itself the mentioned above prefix.

Prefixed terms are presented wider in nanocomputer terminology. The total number of such terms is 43 special lexical units (58,10 % of the total number), for example, bio-computer, qubit. We note that the greater quantity of nanocomputer terminology have terms formed by prefixal method using the prefix "nano", for example, nanochip, nanobots, nanostructure, nanoelectronics, nanosensor. By using this prefix, 32 nanocomputer terms were formed (43,23 % of the total).

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Table 7

Nanocomputer prefixed terms

Despite the fact that in the course of this analysis, we have not found the regular ways of semantic term formation in the nanocomputer sublanguage (terminologization, the expansion and contraction of values, the metaphorization and metonymization). We are of the opinion that "the most typical and productive way of formation of scientific terms is the semantic method" [10, p. 91], because we have found that in this terminology through the metaphor the terms appear, the foundation of which is mankind, for example, smart composites, smart materials, intelligent molecules.

All terms belonging to the computer technology entering the nano terminology, acquire a new specific meaning. The terminology in this area is characterized by the internationalization of terms and intersystem borrowing. The internationalization of terms of nanocomputer technology reflects the fact that the creation of new terms occurs, as a rule, through the use of Greco-Latin or international terminoelements. Intersystem borrowing of terms of this area can be explained by the interdisciplinary of computer technology and nanotechnology.

The results of the study allow ud to conclude that the most productive external source of Russian terms of nanocomputer sublanguage is the semantic calques, this is determined by the influence of English equivalent, and the initial stage of development of Russian nanoсomputer terminology. Analysis of the terms of this sublanguage has also shown that the most productive internal way of term formation is morphological (prefixed).

As the forementioned, we can conclude that the development of nanotechnology and Informatics, replace the prefix micro - to nano – in Informatics are the cause of formation and development of nanocomputer terminology. For example, the term nanocomputer is present in the dictionary of computer terms and dictionary of nanotechnology and nanotechnology-related terms. In our study we analyzed a number of 2589 computer and nanotechnology terms, trying to determine which of the terms belong to nanotechnology, and which of them belong to computer science. Having considered examples of nanocomputer lexical units, it is possible to assert with confidence that the terms denoting the names of new concepts and phenomena in the nanocomputer technology overlap with information science and nanotechnology at 100%. Most of computer terms getting into the nanocomputer terminology, enhance their values, i.e. increase the volume of their semantic concepts, without saving its graphic form as a result.

Thus, the terms that we studied allow us to conclude that the formation and development of the nanocomputer technology as a division of nanotechnology and Informatics is the next logical step in computer science. In applied problems, in our opinion, the basic attention will be given to problems of nanoelectronics and further development and progress of semiconductor technology and information applications (creation of new types of integrated circuits, memory devices, etc.). All this will contribute to the emergence of new terms and create a wide range of activities for linguists in questions of systematization and unification of the terminology system of the nanocomputer technology.

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Bibliographic list

1.Ahmetov M. A. Vvedenie v nanotehnologii. Himija. Uchebnoe posobie dlja uchashhihsja 10–11 klassov srednih obshheobrazovatel'nyh uchrezhdenij. — SPb: Obrazovatel'nyj centr «Uchastie», 2012. — 108 p.

2.Fel'dbljum V. Sh. «Nano» na styke nauk: nanoobekty, nanotehnologii, nanobudushhee: Jelektronnoe mezhdisciplinarnoe izdanie. — Jaroslavl', 2013. — 268 p.

3.Alimuradov O. A., Latu M. N., Razduev A. V. Osobennosti struktury i funkcionirovanija otraslevyh terminosistem (na primere terminosistemy nanotehnologij) / //

International Journal of Experimental Education. 2012. № 2. — P. 86-88.

4.Jashina T. V. Disciplinarnye i mezhdisciplinarnye puti razvitija terminologicheskogo apparata v innovacionno-tehnicheskom diskurse // Vestnik Volgogradskogo gosudarstvennogo universiteta. Serija 2, Jazykoznanie. – 2012. – № 2 (16). – P.106–112.

5.Superanskaja A. V., Podol'skaja N. V i dr. Obshhaja terminologija. Voprosy teorii / Otv.red. T. L. Kandelaki. Izd. 6-e. — M: Knizhnyj dom «Librokom», 2012. — 248 p.

6.Levina M. A. Specifika metaforicheskih perenosov v otraslevoj terminosisteme / M. A. Levina // Nauchnyj vestnik Voronezh. gos. arh.-stroit. un-ta. Sovremennye lingvisticheskie i metodiko-didakticheskie issledovanija. — 2007. vyp. 1 (8). — P. 146–150.

7.Ivanova O. B. Dinamika stanovlenija terminologii novoj predmetnoj oblasti (na materiale terminosfery nanotehnologii v anglijskom i russkom jazykah): avtoref. dis. kand. filol. nauk. — M, 2010. — 24 p.

8.Danilenko V. P. Russkaja terminologija: Opyt lingvisticheskogo opisanija. — M.: Nauka, 1977. — 246 p.

9.Grinev-Grinevich S. V. Terminovedenie: ucheb. posobie. — M.: Akademija, 2008. —

303 p.

10.Velikoda T. N. Processy terminologizacii kak otrazhenie nauchnoj kategorizacii dejstvitel'nosti / T. N. Velikoda // Nauchnyj vestnik Voronezh. gos. arh.-stroit. un-ta. Sovremennye lingvisticheskie i metodiko-didakticheskie issledovanija. — 2010. vyp. 1(13). — P. 88-94.

Analyzed sources

1*. Cresset – ساربن Glossary of terms of computer science and computer engineering, URL: https://www.esi.dz/index.php/english/3034-2016-09-25-08-25-32 (accessed 06.12.2016).

2*. Glossary of nanotechnology and related terms, URL: http://eng.thesaurus.rusnano.com/ (accessed 06.12.2016).

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UDC 81’322.4+004.9

State University of Pridnestrovie,

PhD of Philology, Associate professor, the head of the Chair of foreign Languages of Philological faculty, Uliya Ivanovna Nazarchuk

e-mail: kasyanova-2005@mail.ru

U.I. Nazarchuk

ELECTRONIC RESOURCES AND COMPUTER PROGRAMS

IN TRANSLATION ACTIVITY OPTIMIZATION

The modern information technologies, which are necessary for the work of an interpreter are considered in the article. The ability to apply electronic means help to optimize the work of interpreters and it considerably increases their competitiveness. This article deals with the electronic resources and computer programs used in the translation activity to which the multilingual and monolingual electronic dictionaries, machine translators, systems of the class Translation Memory, the program of automatic editing and processing of texts and the other tools facilitating and accelerating the work of an interpreter are investigated. Various points of view and also advantages and disadvantages of the presented electronic resources are represented here. Such electronic resources help an interpreter to optimize the process of translation.

Keywords: an interpreter , machine translation, an electronic dictionary, global Internet, morphological description, general availability, Internet resources, bilingual dictionaries.

Under the conditions of constant volume increase of translated texts the question of maintaining of a high quality translation at a steadily increasing speed of its accomplishment came up. Today, it is the information and communication technologies that are, firstly, a powerful tool to optimize the translation as a process and, secondly, effective and accessible means of quality control over translation as a result.The purpose of this work is to analyze the existing electronic systems in online and offline mode, programs of machine translators, terminology databases of data, etc. To characterize advantages and disadvantages of the Internet resources which are most extended. This information will help a translator to be guided quickly in the choice of the necessary resource.

This subject of the research can be considered quite modern as the history of development and implementation in everyday life of personal computers contains hardly more than twenty five years. This subject acquires special relevance because nowadays Pridnestrovye is more and more integrated into the international community and that along with economic and political barriers it is interfered in many respects by linguistic barriers. At the same time, there aren't much professional translators, who are capable and interested to perform this process of communication in all spheres of science and culture. It was a consequence of the fact that at this stage training process of the professional translator takes a lot of time and is very laborconsuming. Therefore, search of ways as much as possible is especially urgent right now to automate the process of translation, performed by the person on the one hand as much as possible to facilitate hard work of the translator, and with another - to make this work the most effective. It is possible to perform similar only as much as possible having integrated efforts of specialists in areas of information technologies and linguistics.

_____________________

© Nazarchuk U.I., 2016

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Scientists have tried for a long time to create automatic machine translators that operate without human intervention. And although at this level of development the complete automation of translation process isn’t possible, the translators’ activity of the new millennium has become unthinkable without the use of new information technologies and electronic instruments which are aimed to accelerate and facilitate the translation process, including

-the electronic multi-language translations and monolingual online or offline dictionaries;

-automatic machine translators (the most famous are the PROMT company software products); Translation Memory class system (TRADOS, Déjà Vu, Wordfast, etc.);

-automatic text editing program; electronic libraries; electronic encyclopedias; electronic dictionaries (Lingvo, "MultiLex", "Multitran", "Context», Polyglossum);

-terminology databases; and, finally,

-the global Internet as an incredible volume storage of information resources.

For example, A.N. Usacheva emphasizes that with the appearance of Internet, the translator acquired the unique opportunity to enter into the global information network, and the data from anywhere became available for him. The changes that appeared in the translator profession are so enormous that now it is hardly possible to estimate all their consequences"[1]. The ability to apply all of the above listed and the other electronic tools, allows to optimize the work of translators (especially written) and increase their competitiveness in the translation services market.

In this article we will try to explore some advantages and disadvantages of these online resources.

Machine translation systems make an automatic translation of the text. Words or phrases are the units of such translation, and the last systems take into account the morphology of the translated word. “The developed machine translation systems make the translation according to the translation algorithms which are set by the developer and/or corrected by the user” [2]. To translate the text some special program should be installed in the computer. This program allows to realize the translation algorithm which is understood as the sequence of clearly and strictly defined action over the text in order to find the translation equivalents in the language pair Lng1-Lng-2 for a given translation direction. Such system includes “the bilingual dictionaries supplied with the necessary grammatical information (morphological, syntactic and semantic) for the transfer of equivalent, variant and transformational translation equivalents, as well as the algorithmic means of grammatical analysis, realizing any of the accepted formal grammars for automatic text revision” [3].

There are also the other machine translation systems, which can translate in three or more languages, but they are experimental at the moment.

In the modern world there are two concepts of machine translation systems develop-

ment:

The first system is a model of a large dictionary with a complex structure, which is built into the most of modern programmatic translators;

The second model is a model “meaning-text”, first introduced by A.A. Lyapunov, but it isn’t yet implemented in any product[4].

At the present stage there are such known systems as PROMT, Retrans Vista and So-

crat.

In a system such as PROMT program builder developed a unique complete morphological description of all the languages with which the system can work. For the Russian language it contains 800 types of inflection, for French and German more than 300 types, as well as for English which is not inflected language, it contains more than 250 types of inflection. As the set of endings for each specified language is stored in the form of tree structures, it provides not only an efficient storage method, but also an effective algorithm of morphological analysis.

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The idea of the translation process as a process with an object-oriented organization based on the hierarchy of the offer processed components is in the main principles of these systems. This idea differs from the accepted linguistic approach, which is based on the separation of successive analytical and synthetical processes of proposals. And it made the PROMT system sustainable and inclusive. The advantage of this approach is the use of various formalisms to describe the translation of the different levels. The PROMT system represents the network grammars which are similar by type with the advanced network transitions, and procedure oriented filling algorithms and transformation of frame structures for the analysis of complex predicates. The description of lexical unit in the dictionary entry, which is not limited in size, contains a lot of different features closely related to the structure of algorithms, and which works not on the basis of the eternal antithesis of the syntax - semantics, but on the basis of levels of text components. And what is more these systems can work with not fully described dictionary entries, this is a huge advantage. This is an important point when you open a dictionary to the user, which cannot be required the delicate treatment of linguistic material. There is also the lexical units level, the groups level, the level of simple and complex sentences in this system. All these processes collaborate hierarchically in accordance with the hierarchy of text units, exchanging of the synthesized and inherited attributes. Their interaction allows using the different formal describing methods of the algorithms of different levels.

Further we’ll look at the advantages and disadvantages of electronic dictionaries. How do they differ from the machine translation?

Electronic Dictionary – is a computer database containing the dictionary entries coded in a special way, which allows you to search quickly for words. This search is based on morphological combinations, and with the possibility of changing the translation direction, e.g., from Russian to English or vice versa [5].

The main difference between the electronic dictionaries and machine translation systems is that the electronic dictionary provides to the translator the entire spectrum of definition of the desired word or phrase listed in its database. Thus, this dictionary gives a person the right to select the appropriate variant by one’s self, while the machine translation system automatically selects the variant from the database based on the built-in algorithms.

ABBYY Lingvo - is the next member of the family of electronic dictionaries, created by the Russian company ABBYY. The volume of dictionary entries is more than 8.7 million. units. Multilingual version includes 12 languages (Armenian, Russian, Ukrainian, English, German, French, Spanish. Italian, Turkish, Latin, Chinese and Portuguese). This dictionary doesn’t provide the full translation function, but it’s possible to translate the texts word by word from the clipboard. In some dictionaries professional speakers make the synchronizing of the words. All versions of this dictionary contain English definition dictionary (Oxford and Collins) Ephraim TF Dictionary of Russian language.

ABBYY Lingvo Users have the possibility to create their own dictionaries and share them. Dictionaries are selected, and the best ones are available on the website for public use[6]. Thus, the process of updating and expanding of the vocabulary base is under constant supervision of professional lexicographers. It is undoubtedly one of the main benefits of the dictionary.

Multitran dictionary is the complete antithesis to the above one. Anybody who wants can add the definitions to this dictionary, and it happens without any control. It's enough to register on this web-site, select the appropriate option, and enter the text. It works awfully from the lexicographical point of view. There is chaos everywhere:

in the system of word labels,

in the division on the subject headings,

in the classification of words by parts of speech, in the amount of mistakes and misprints variety.

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Moreover, it is hardly fair to criticize and condemn from the classic lexicographical positions the product that, strictly speaking, isn’t a dictionary, and is called so only for the reason of brevity and convenience. The starting point for the popularity of Multitran is, apparently, its accessibility. This is a free dictionary. If you want, you can buy the server version of the dictionary for use in the organization. And another undoubted advantage of this resource, because of which it is highly valued and widely used by translators, is the enormous volume of the An- glo-Russian Dictionary which contains about 4.5 million terms!

However, there are a lot of inaccuracies among them, which are penetrating to the dictionary caused by the user error or the outdated dictionaries. But among the Multitran patrons there are a lot of professional translators, who add to the dictionary only the verified variants of translations and who report about the errors in dictionary entries [7]. Thank to this interactive dictionary together with a huge audience through Multitran there is a constant alive exchange of translation experience. Several thousand translation community shares with the vocabulary the fruits of their translation experience. Having conducted the research it is possible to draw a conclusion that Multitran is characterized by the variety of filling and it covers much more possible contexts than Lingvo does. Having compared, the author comes to the conclusion that the dictionary is largely built on the accumulation of real translation experience, because its dictionary entries are so vast and varied. They, like the rest of the dictionary, are not perfect, but they are more likely appropriate for the translators, more likely that they can find what he needs in Multitran than, for example, in Lingvo.

We summarize the main advantages of Multitran dictionary:

High volume;

Variety of translation variants;

Constant filling;

The possibility of mistakes messages;

A vast audience, sharing their experiences;

Accessibility.

As well as Lingvo, Multitran - is a system for translators, which, in addition to the dictionary, includes parallel texts database (originals and the other proposal of translations), a links list of useful resources (articles, reference materials, translated samples of documents), a reading room (foundational works collection in electronic form).

It should be noted that there is such dictionary as the Dictionary MultiLex - electronic dictionaries family from the company CJSC "MediaLingua", 1996-1998. At the present time the dictionaries for the major European languages are published. MultiLex – is dictionary polyglot. It is indispensable for those who translates from English, French, German, Spanish, Italian and even Turkish and Tatar. The seventh dictionary edition on the disk with the largest amount of translations - 10 million (it’s possible to buy edition of 6 million, 60 thousand, 40 thousand or 24 thousand...). Program is released in 3 versions - for beginners, experts and professionals [8].

In MultiLex dictionary a student-translator can search for phrases and examples of words usage for request, containing one or more members of the phrases in any order. The "mixed" requests containing words in both languages are also permitted that. MultiLex is able to search on a Latin word. This can be useful for those who need to find a botanical and zoological nomenclature.

MultiLex provides a voice for the titles of all dictionary entries via text-to-speech program that is disadvantage for this dictionary. MultiLex developers also launched a pocket electronic translator which contains 1 million words. It contains replicas of V.K. Mueller and A.I. Smirnitsky dictionaries in order to work with the Russian and English texts. It completes translation of words and phrases from Russian into English and vice versa. There is also English

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