Machine translation, or rather computer translation, is also a written translation, since as a result we receive a written text. However, it is not carried out by a translator, but by a special computer program. Modern computer translation programs are quite advanced, but they still cannot solve the most difficult task of the translation process: the choice of a contextually necessary option, which in each text is determined by many reasons. Currently, the result of this type of translation can be used as a draft version of the future text, which will be edited by the translator, and also as a means to get a general idea of the topic and content of the text in extreme situations where there is no translator.
An even more difficult task is translating spoken text using computer programs, since the problem of recognizing spoken speech is only at the initial stage of its solution. Until now, an insurmountable obstacle is the individual coloring of the sound of a speech segment - in any language such speech is poorly formalized.
Preliminary editing of the syntactic structure may include:
· splitting an extra-long sentence (more than 40 words) into several shorter ones, adding (if necessary) connective elements;
· introducing articles into the English text where necessary or grammatically justified;
· repetition of elements in the coordinating connection of phrases in a sentence;
· introducing conjunctions when using non-union connections between sentences;
· eliminating constructions in brackets in the middle of a noun phrase or in the middle of a sentence;
· replacing occasional abbreviations with full names or introducing special characters that do not allow their translation;
· eliminating lexical and logical ellipses, informal constructions and metaphors;
· bringing to a single form constructions or complex words that may appear in the text in continuous, hyphenated and free writing.
The manually edited text is then automatically processed in the MP system.
25. General scheme of machine translation.
All over the world, the use of machine translation systems, despite all their weaknesses, has long been an element of the professional work of a translator, who must be able to use a computer not only as a typewriter. The concept of an automated translator's workstation, including a complex of resident dictionaries, thesauruses, spell-checking systems, systems for accessing information over various data networks, should become common knowledge for a philologist.
A machine translation (MT) system for texts can be used as part of such an automated translator workstation, providing high-quality translation that is strictly focused on a specific subject area, user tasks and type of documentation. In addition, such a system can help a user who does not know a foreign language very quickly and at low cost obtain an approximate (rough) translation of texts in the field of knowledge that interests him, a translation sufficient to understand the information transmitted by text in foreign language.
General requirements for practical systems
machine translation (MT)
· System stability. The MP system should produce a result that can be used even in the case of defects in the source material and incomplete vocabulary.
· Replication of the system. The system should have fairly simple software and linguistic tools to expand the scope of its application.
· System adaptability. The MP system must have the means to customize it to the needs of specific users and the characteristics of the documents being processed.
· Optimal timing parameters. The speed of text translation must correspond either to the volume of information received per unit of time, or to the user’s work standards.
· User comfort. The service facilities of the system must ensure user convenience in all operating modes possible in the system.
When working with a specific machine translation system, you need to remember that translation is carried out at several subordinate levels of the system implementation.
In general, these levels include:
· level of automatic text pre-editing;
· level of lexical-morphological analysis;
· level of contextual and group analysis;
· level of analysis of functional segments;
· level of proposal analysis;
· level of synthesis of the output text;
· level of automatic post-editing.
SUBJECT, OBJECT AND TASKS OF LINGUISTIC THEORY OF TRANSLATION
Currently, the linguistic theory of translation is firmly established as an independent scientific discipline. However, a number of fundamental issues that determine the status of translation theory still remain unresolved. One of these questions is the question of the subject and object of translation theory.
Various, often opposing points of view have been expressed in the literature regarding what should be considered the subject and object of translation theory. Thus, I.I. Revzin and V.Yu. Rosenzweig argue that the object of translation is the translation process itself, during which a transition is made from one system of signs to another and which can be described in semiotic terms 86. These authors make a fundamental distinction between the translation process and the translation result. They proceed from the fact that traditionally the science of translation was built as a normative science, the main goals of which were to establish the result of translation and develop criteria for assessing the quality of translation. The normative theory of translation was built empirically, based on a comparative analysis of originals and translations. Theoretical principles were borrowed from lexicology, grammar, stylistics and literary criticism. With this approach, according to I.I. Revzin and V.Yu. Rosenzweig, a theoretical understanding of the translation process cannot be achieved. Science that seeks to describe
"Revzin I. I., Rosenzweig V. Yu. M.: Higher. school, 1964. P.21.
68 V.V.Sdobnikov, O.V.Petrova♦ TRANSLATION THEORY
Translation as a process should not be normative, but theoretical. That is, it should describe not what should be, but what is inherent in the very nature of the phenomenon 87.
A.D. Schweitzer disagreed with this point of view, and believes that such a sharp contrast between theoretical and normative approaches is hardly justified. Excluding the results of the translation process from consideration unduly narrows the subject of translation theory and hardly contributes to identifying its essence. According to A.D. Schweitzer, translation is a purposeful activity that meets certain requirements and standards and is focused on achieving a certain result. These standards reflect value orientation the translator, without which it is impossible to satisfactorily explain the logic of translation decisions 88 . Thus, A.D. Schweitzer includes in the subject of translation theory both the translation process itself and the result of the translation process.
It seems that translation researchers, trying to define the subject of translation theory, did not fully take into account the fact that translation is a complex, complex phenomenon, which is influenced by many diverse factors. Understanding of this circumstance is achieved to a greater extent in the works of V.N. Komissarov, who quite rightly notes that it is hardly legitimate to contrast the translation process with its result. It is the result of translation that represents that directly observable reality, based on the analysis of which one can indirectly judge how the translation process proceeded, which is inaccessible to direct observation.
"Revzin I. I., Rosenzweig V. Yu. Fundamentals of general and machine translation. M.: Higher. school, 1964. P.21.
"Schweitzer A.D. Translation theory: status, problems, aspects. M: Nauka, 1988. P.7.
PART II. Translation theory as a scientific discipline 69
The linguistic theory of translation deals both with texts in the source language (SL) and the target language (TL), and with the very process of converting the original text into the target text. But this approach is not entirely sufficient. Translation activities, by definition, are intermediary in nature. Translation provides the possibility of interlingual communication. This means that in order to create a full-fledged translation, the translator must take into account the characteristics of the author of the original message and the recipients of this message, their knowledge, experience, as well as the peculiarities of perception of the people for whom the translation is intended, etc. all other aspects of interlingual communication that affect the course and result of the translation process. This means that the subject of translation theory is complex and is not limited only to the translation process and its result. The linguistic theory of translation considers translation within the broad framework of interlingual communication and studies all its aspects and determining factors, both linguistic itself and external to the language, but directly or indirectly influencing the choice of linguistic units in the translation process 89 .
From this presentation of the problem it is clear that there is no unity among translation researchers regarding the terminology used. First of all, attention is drawn to the lack of a clear distinction between the concepts of subject of scientific research and object of scientific research. By the way, the analysis of definitions offered by Russian language dictionaries also does not bring greater clarity to this issue. For example, subject scientific research is defined as “a topic, something that serves as the content of thought, speech, what cognitive or creative activity is aimed at
89 Komissarov V.N. Translation theory (Linguistic aspects). M.: Higher. school.., 1990. P.40-41.
70 V.V.Sdobnikov, O.V.Petrova♦ TRANSLATION THEORY
Activities" 99. An object is defined as “that which confronts the subject, towards which his objectively practical and cognitive activity is directed” 100. As we see, both concepts are defined as something towards which practical, cognitive and creative activity research subject. At the same time, it would be advisable to consider as an object of research what really belongs to the circle of material phenomena of the world, and as a subject of research - a certain problem, the solution of which Scientific research actually directed. Based on this, nog the object of the linguistic theory of translation we will understand the intermediary translation activity within the framework of interlingual communication, represented both directly (process) and indirectly, that is, reflected in the results of the translation process. The subject of translation theory is the study of the laws of the translation process, the factors influencing the course of the translation process and determining the result of the translation.
V.N. Komissarov 101 formulates the following tasks linguistic theory of translation:
1) reveal and describe general linguistic os
new translations, i.e. indicate what features of the language
logical systems and patterns of functioning
languages form the basis of the translation process
sa, make this process possible and determine
its character and boundaries;
2) define translation as a linguistic object
who is researching, indicate its difference from others
types of language mediation;
3) develop the basis for the classification of types of pe
reproductive activities;
99 Dictionary of the Russian language in 4 volumes. Volume III. M.: Russian language, 1983. P.366. ""Dictionary of the Russian language in 4 volumes. Volume 11. M: Rus. lang., 1983. P.579. 101 K o m i s s a r o v V.N. Translation theory (Linguistic aspects). M.: Higher school.., 1990. P.35-36.
PART II. Translation theory as a scientific discipline 71
4) reveal the essence of translation equivalence as the basis for the communicative equivalence of the original and translation texts;
5) develop general principles and features
construction of private and special theories of translation
yes for various language combinations;
6) develop general principles of scientific inventory
understanding the translation process as translator's actions
on converting original text into rewritten text
water;
7) reveal the impact on the translation process
pragmatic and sociolinguistic factors;
8) define the concept of “translation norm” and how
work principles for assessing the quality of translation.
Our course will be structured in accordance with these objectives. general theory translation. But first we should consider the issue of the approximate composition of translation studies and the linguistic theory of translation.
Translation studies as a scientific discipline is broader than translation theory and includes several scientific disciplines, or sections. Translation studies include translation theory, history of translation activity, translation criticism, translation lexicography, translation didactics (methods of teaching translation). As we see, the linguistic theory of translation is only one of the sections of translation studies, but at the same time it is complex in nature and includes the following sections:
General theory of translation- a section of the linguistic theory of translation that studies the most general linguistic patterns of translation, regardless of the specific pair of languages involved in the translation process, the method of carrying out this process and the individual characteristics of a specific act of translation.
Special theory of translation- a section of the linguistic theory of translation that studies the features of the process of translating texts of different types and influences
72 V.V.Sdobnikov, O.V.Petrova♦ TRANSLATION THEORY
This process is influenced by speech forms and the conditions for its implementation. Several special translation theories can be distinguished: the theory of literary translation, the theory of scientific and technical translation, the theory of oral translation, the theory of machine translation, etc.
Particular theory of translation- a section of the linguistic theory of translation that studies the linguistic aspects of translation from one given language to another given language. There can be many particular theories of translation: the theory of translation from English into Russian, the theory of translation from German language into Japanese, theory of translation from French in Swahili, etc.
RELATIONSHIP OF TRANSLATION THEORY WITH OTHER LINGUISTIC DISCIPLINES
The linguistic theory of translation is closely related to such linguistic disciplines as contrastive linguistics, sociolinguistics, psycholinguistics, and text linguistics.
Translation theory and contrastive linguistics
Contrastive linguistics is a direction of research in general linguistics, the purpose of which is the comparative study of two, or less often several, languages in order to identify their similarities and differences at all levels of the linguistic structure 102. As A.D. Schweitzer notes, the issue of the relationship between contrastive linguistics and translation theory still continues to be a subject of debate. In the past, there was often no clear differentiation
102 Linguistic encyclopedic Dictionary. M: Sov. encyclopedia, 1990. P.239.
. Translation theory as a scientific discipline 73
Recognition of these disciplines. J.I. Retzker wrote back in 1950 that “translation... is unthinkable without a solid linguistic foundation. Such a basis should be a comparative study of linguistic phenomena and the establishment of certain correspondences between the original language and the target language. These correspondences in the field of vocabulary, phraseology, syntax and style should form the linguistic basis of the theory of translation” 103. Thus, the comparison of languages and linguistic phenomena was actually identified with the linguistic theory of translation.
Sometimes the theory of translation is identified not with contrastive linguistics in general, but with one of its sections, namely: with comparative stylistics. This tradition was founded by the work of J.-P. Vinet and J. Darbelne “Comparative stylistics of the French and English languages” (1958), in which the authors actually equated the concepts of comparative stylistics and translation theory. This feature of linguistic translation research was later paid attention to by both I.I. Revzin and V.Yu. Rosenzweig: “Recognizing the value of the works of this direction for the theory of translation, ... one cannot fail to notice the confusion in them of the concepts of stylistics and translation theory.” 104. And yet, even a decade later, some researchers argued that “the linguistic theory of translation is nothing more than “comparative linguistics of the text,” that is, the comparative study of semantically identical multilingual texts” 105.
The close connection between contrastive linguistics and translation theory is indicated by the very description of the method.
103 Sh veytser A. D. M:
Science, 1988. SY.
104 R e v z i n I. I., Rozentsveyg V. Yu. Fundamentals of general and machine
translation. M.\ Higher school, 1964. P.32.
105 B a r h u d a r o v L. S. Language and translation (Issues of general and specific
translation theory). M.: Intl. relations, 1975. P.28.
74 V.V.Sdobnikov, O.V.Petrova♦ TRANSLATION THEORY
Comparative language learning. The principles of comparative description are formulated by A.V. Fedorov as follows: “What is specific to a particular language is not the expressed meaning that it has in common with another language, but the formal categories in which it is expressed, the structural features. From a formal category, as from an objective given (for example, from a certain type of words, word-formation models, from word order, from two-part sentences with a certain type of subject, etc.), the researcher goes to determine its meanings in one language and then to those expressing these meanings to formal means of another language (matching or different types of words, the same or different word order, two-part or one-part sentences, etc.). Naturally, with this method of analysis, the translation material is very grateful...” 106. From this definition of the research method it follows that linguists, in the interests of comparative research of languages, used the method of comparing specific speech works in different languages, which are actually originals and translations. This is fully consistent with the statement of E. Coseriu that contrastive linguistics is at the level language norm, which examines the actual use of functional units, covers exactly the area in which the translation process takes place and coincides with it. According to E. Coseriu, the area closest to the theory of translation is precisely that area of contrastive linguistics, which is focused on language in action. Like translation theory, this area deals with speech implementations of language structure, with the area of language functioning in speech, and, like particular translation theory, it is unidirectional (for example, the problem of finding
106 Quoted. by: RevzinI. I., RosenzweigV. YU. Fundamentals of general and machine translation. M.: Higher. school.., 1964. P.33
PART //. Theory translation as a scientific discipline 75
Correspondence to gerunds is relevant only for translation from Russian and for contrastive linguistics, the source language of which is Russian) 107.
Data from contrastive linguistics are undoubtedly useful for the linguistic theory of translation. By exploring the relationship between the functional units of language A and language B, contrastive linguistics creates the necessary foundation for building a theory of translation. In fact, many translation transformations that make up the “technology” of translation ultimately go back to the functional and structural differences between languages that “collide” with each other in the process of translation. Contrastive linguistics in a number of cases answers the question of why this or that operation is carried out in translation 107 . One of the reasons for using translation transformations is the presence in one of the interacting languages of so-called “non-equivalent forms”, the identification of which is facilitated by the data of contrastive linguistics.
We can say that translation theory needs contrastive linguistics as a source of initial data. These data, which shed light on the discrepancies between structural types, systems and norms of languages, serve as a starting point for translation analysis proper 108.
Despite the close connection between contrastive linguistics and translation theory, they cannot be equated with each other. The task of contrastive linguistics is to compare languages and identify their similarities and differences. Translation theory, in turn, studies translation as a specific type of interlingual communication, language mediation. Its goal is to identify the essence, translation, its
107 Sh veytser A. D. Translation theory: status, problems, aspects M:
Science, 1988. SP.
108 Ibid. P.12.
76 V.V.Sdobnikov, O.V.Petrova♦ TRANSLATION THEORY
Mechanisms, methods of implementation, linguistic and extralinguistic factors influencing it. The theory of translation, in addition to the source and final texts, takes into account the sociocultural and psychological differences between multilingual communicants, as well as a number of other sociocultural and psycholinguistic determinants of the translation process. It is taken into account that translation is not a simple change of language code, but also an adaptation of the text for its perception through the prism of another culture.
Approaches to machine translation
Machine translation systems can use a translation method based on linguistic rules. The most suitable words from the source language are simply replaced with words from the target language.
It is often argued that to successfully solve the problem of machine translation, it is necessary to solve the problem of understanding text in natural language.
Typically, a rule-based translation method uses a symbolic representation (an intermediary) from which the text in the target language is created. And if we take into account the nature of the intermediary, we can talk about interlinguistic machine translation or transfer machine translation. These methods require very large dictionaries with morphological, syntactic and semantic information and a large set of rules.
If the machine translation system has enough data, it can produce a good quality translation. The main difficulty lies in generating this data. For example, large text corpuses are necessary for statistical methods translation, for translation based on grammar, turn out to be insufficient. Moreover, for the latter, an additional grammar task is required.
To translate related languages (Russian, Ukrainian), a simple substitution of words may be sufficient.
Modern systems machine translation is divided into three large groups:
· rules-based;
based on examples;
Rule-based EMS
Rule-based machine translation systems are a general term that refers to machine translation systems based on linguistic information about the source and target languages.
They consist of bilingual dictionaries and grammars covering the basic semantic, morphological, syntactic patterns of each language. This approach to machine translation is also called classical.
Based on this data, the source text is sequentially, sentence by sentence, converted into the target text. Often, such systems are contrasted with machine translation systems that are based on examples.
The operating principle of such systems is the connection between the structure of the input and output sentences. The translation is not of particularly good quality. But it works in simple examples.
Translation from English to German would look like:
A girl eats an apple. Ein Madchen isst einen Apfel.
These systems are divided into three groups:
· word-by-word translation systems;
· transfer systems;
· interlinguistic;
Word by word translation
Such systems are now used extremely rarely due to the low quality of translation. The words of the source text are converted (as is) into words of the target text. Often such a transformation occurs without lemmatization and morphological analysis. This is the simplest machine translation method. It is used for translation long lists words (for example, directories). It can also be used to compile a subscript for TM systems.
Transfer systems
How transfer systems, and interlinguistic, have the same general idea. To translate, it is necessary to have an intermediary who carries the meaning of the expression being translated. In interlinguistic systems, the intermediary does not depend on the pair of languages, while in transfer systems it does.
Transfer systems operate on a very simple principle: rules are applied to the input text that match the structures of the source and target languages. The initial stage of work includes morphological, syntactic (and sometimes semantic) analysis of the text to create an internal representation. The translation is generated from this representation using bilingual dictionaries and grammatical rules. Sometimes, based on the primary representation that was obtained from the source text, a more “abstract” internal representation is built. This is done in order to emphasize places that are important for translation, and discard unimportant parts of the text. When constructing a translation text, the transformation of the levels of internal representations occurs in the reverse order.
When using this strategy, fairly high quality translations are obtained, with an accuracy of around 90% (although this greatly depends on the language pair). The operation of any transfer transfer system consists of at least five parts:
· morphological analysis;
· lexical transfer;
· structural transfer;
· morphological generation.
Morphological analysis. Words in the source text are classified by parts of speech. Their morphological characteristics are revealed. Word lemmas are defined.
Lexical categorizations. In any text, some words may have more than one meaning, causing ambiguity in the analysis. Lexical categorization reveals the context of a word. Various kinds of notes and clarifications are possible.
Lexical transfer. Based on a bilingual dictionary, the lemmas of words are translated. The action is very similar to word-by-word translation.
Structural transfer. The words agree in a sentence.
Morphological generation. Based on the output data of the structural transfer, word forms of the translated text are created.
One of the main features of transphenial machine translation systems is the step during which an intermediate representation of the source language text is “transferred” into an intermediate representation of the target language text. This can work at one of two levels of linguistic analysis, or at both.
1. Superficial (syntactic) transfer. This level is characterized by the transfer of “syntactic structures” between the source and target languages. Suitable for languages in the same family or type, for example in Romance languages, between Italian Spanish, Catalan, French, etc.
2. Deep (semantic) transfer. The level is characterized by a semantic representation. It depends on the original language. This representation may consist of a number of structures that represent meaning. Translation also usually requires a structural transfer. This level is used for translation between more distant languages.
Interlinguistic machine translation
Interlinguistic machine translation is one of the classical approaches to machine translation. Original the text is transformed into an abstract representation that is independent of language (unlike transfer translation). The translated text is created based on this representation. The main advantage of this approach is that it allows you to add a new language to the system. It can be proven mathematically that within the framework of this approach, the creation of each new language interpreter for such a system will reduce its cost, compared, for example, with a transfer translation system. In addition, within this approach it is possible
· implement “text retelling”, paraphrasing the source text within one language;
· relatively simple implementation of translation of very different languages, such as Russian and Arabic.
However, there are still no implementations of this approach that would work correctly for at least two languages. Many experts express doubts about the possibility of such implementation. The biggest challenge for creating such systems is designing an interlingual representation. It must be both abstract and independent of specific languages, but at the same time it must reflect the features of any existing language. On the other hand, within artificial intelligence, the task of highlighting the meaning of the text on this moment still not resolved.
The interlinguistic approach was first proposed in the 17th century by Descartes and Leibniz, who proposed universal dictionaries using numerical codes. Others such as Cave Beck, Athanasius Kircher and Johann Joachim Becher worked to develop an unambiguous universal language based on the principles of logic and iconography.
In 1668, John Wilkins, in his treatise “An Essay on Genuine Symbolism and Philosophical Language,” spoke about his interlingua.
During the 18th and 19th centuries, many universal languages were developed, including Esperanto. It is known that the idea of a universal language for machine translation did not manifest itself in any way in initial stages development of this technology. Instead, only pairs of languages were considered. However, during the 1950s and 60s, researchers in Cambridge led by Margaret Masterman, in Leningrad led by Nikolai Andreev and in Milan by Silvio Ceccato began work in this area.
In the 1970s and 1980s, some progress was made in this area and a number of machine translation systems were built.
In this translation method, interlingual representation can be seen as a way of describing the analysis of a text in the original language. At the same time, the morphological and syntactic characteristics of the text are preserved in the representation. It is assumed that in this way the “meaning” can be conveyed when creating a translated text.
In this case, two interlingual representations are sometimes used. One of them more reflects the characteristics of the source language. The other is the target language. The translation in this case is carried out in two stages.
In some cases, two or more representations of the same level are used (equally close to both languages), but differing in topic. This is necessary to improve the quality of translation of specific texts.
This approach is not new to linguistics. It is based on the idea of the proximity of languages. To improve the quality of translation, natural language is used as a bridge between two other languages. For example, when translating from Ukrainian to English, Russian is sometimes used.
To use the interlinguistic machine translation system you need:
· dictionaries for analysis and generation of texts;
· description of language grammars;
· knowledge base of concepts (to create an interlingual representation);
· rules of concept projection for languages and representation.
The hardest part about creating this type is the inability to build a base for broad areas of knowledge. And those databases that are created for very specific topics have high computational complexity.
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41. Quine W. Meaning and Translation. // R. Brower (ed.) On Translation. - Cambridge (Mass.), 1959.
42. Reiss K. Möglichkeiten und Grenzen der Übersetzungskritik. - Munich, 1971.
43. Reiss K.. Vermeer H.J. Grundlegung einer allgermeinen Translationstheorie. Tubingen, 1984.
44. Rose M.D. (ed.). Translation Spectrum. Essays in Theory and Practice. - Albany, 1981.
45. Ross C.D. Translation and Similarity // M.D.Rose (ed.) Translation Spectrum. - Albany, 1981.
46. Savory T. The Art of Translation. - L., 1952.
47. Schleiermacher F. Methoden des Übersetzens // H.J.Störig. Das Problem des Übersetzens. - Stuttgart, 1963.
48. Seleskovich D., Lederer M. Interpreter pour traduire. - Paris., 1987.
49. Snell-Hornby M. Translation Studies. An Integrated Approach. - Amsterdam, Philadelphia, 1988.
50. Sperber D., Wilson D. Relevance: Communication and cognition. - Oxford, 1986.
51. Tirkkonen-Condit S. Textual Criteria in Translation Quality Assessment, - Jyvaskyla, 1982.
52. Toury G. In Search of a Theory of Translation. - TelAviv, 1980.
53. Tytler A.F. Essay on the principles of translation. - L., 1791.
54. Vehmas-Lehto I. Quasi-Correctness. - Helsinki, 1989.
55. Vinay J.-P., Darbelnet J. Stilistique comparée du français et de 1"anglais. - Paris, 1968.
56. Voegelin C.F. Multiple Stage Translation // IJAL. - Vol.20, No.4, 1954.
57. Wilss W. Übersetzungswissenschaft: Probleme und Methoden. - Stuttgart, 1978.
58. Wilss W. Kognition und Übersetzen: Zu Theorie und Praxis der menschlichen und der maschinellen Übersetzung. - Tüsbingen, 1988.
59. Shuttleworth M., Cowie M. Dictionary of Translation Studies. – Manchester, UK: St. Jerome Publishing, 1997. – 234 p.
Paydalangan sozdikter, resmi kuzhattar, okulyktar, audarylgan enbekter:
1. Ayapova Zh.M., Arynov E.M. Isker Adamny Oryssha-Kazakh Economy Tusіndіrme Sozdіgі. A., 1993
2. Egeubay A. Kisilik kitaby. – Almaty, 1998.
3. Ibatov A. Kutbtyn “Khusrau ua Shirin” poem by Masyn Sozdigi (XIV Gasyr). - Almaty, 1974.
4. Ibraeva A. Zan terminderinіn kazaksha-oryssha zhane oryssha-kazaksha kyskasha tussіndіrme sozdіgі. A., 1996
5. Kazakhstan Republic Syn Constitution. A., 1995
6. Kazakhstan Republic Son's Constitution son's body of creation. A., 1996
7. Kaliev G. Tіlіmі terminderің tүsіndіrme сөздігі. A., 2005.
8. Kaliev G., Bolganbaev A. Kazirgі kazakh tіlіnіn lexicology and phraseology. A., 2006
9. Kozhakhmetova Kh.K., T.B. Kazakh-oryssha phraseologylyқ sozdіk. A., 1988
10. Rakhmatullin H. Bank termderin oryssha-kazaksha kyskasha sozdigi. A., 1992
11. Rustemov L.Z. Arab-Iran kirme sozderin kazaksha-oryssha tusindirme sozdіgi. A., 1989
12. Russian-Kazakh proverbs and sayings / Comp. A. Turekhanov and others - A., 1999
13. Sapargaliev G. Zaң terminderіnѣ tүsіndіrme сөздігі. A., 1995
14. Tazkire-i-Bugra Khan - room Serikbay Kosan. – Almaty: Tolagai, 2007.
Paydalangan derekkozder:
1. Abay. Shyғarmalarynyң eki tomdyk tolyk zhinagy. Ekinshi volume. Olender men audarmalar. Poemalar. Kara sozder. A., 1995
2. Altynsarin Ybyray. Eki tomdyk shiғarmalar zhinagay. A., 1988
4. Auezov M. The Path of Abai / Translated by A. Kim. – A., 2007. Book 1.
5. Auezov M. Zhiyrma tomdyk shygarmalar zhinagay. A., vol. XII, 1983, vol. XІX, 1985.
6. Auezov Mukhtar. Abai Zholy: An epic novel. A., 1989.
7. Dzhambul. Selected works. A., 1981
8. Esenberlin I. Almas kylysh (tarihi novel). A., 1971
Lecture 13. Machine translation of text. Computer language dictionaries
Machine Translation Basics
Translation is a type of language mediation that is focused on the foreign language original. Translation is considered as a foreign language form of existence of the message contained in the original. Interlingual communication carried out through translation, in the most to a greater extent reproduces the process of direct speech communication, in which communicants use the same language.
Machine translate is the automatic extraction of knowledge and texts written in natural language using computer programs based on linguistic support.
Machine translation process- these are the actions of a computer to convert text in one natural language into text equivalent in content in another language, as well as the result of such an action.
Automatic text understanding system, proceeds from the fact that a text in natural language, constructed in accordance with dictionaries, grammar and natural language algorithms, based on a semantic network, frames and thesauri, is understood by the user due to the fact that he has linguistic knowledge - syntactical-semantic structures, and also specialized knowledge.
Most automatic language processing systems aim to analyze texts that have been pre-divided into sentences. However, language data is most often available to us in the form of texts divided into paragraphs, chapters and other larger units. Therefore, for their effective automatic analysis, appropriate segmentation algorithms are required.
Tasks when creating a system for automatic text understanding:
· analysis of the source natural text, which ensures the construction of linguistic structures, including various semantic structures, complete, partial, compressed, seeking to present the content of the text in the form databases,
· comparison of linguistic structures of the text with special or individual knowledge, also presented in the form of a database
· generalization of texts based on information contained in traditional relational databases, as well as in conceptual text structures or in individual databases.
For implementation of machine translation A special program is entered into the computer that implements translation algorithm, which is understood as a sequence of unambiguously and strictly defined actions on the text to find translation matches in a given pair of languages when given direction translation (from one specific language to another). There are also separate machine translation systems designed to translate within three or more languages, but these are currently experimental.
Modern machine or automatic translation is carried out with the help of a person: a pre-editor, who in one way or another pre-processes the text to be translated, an inter-editor, who participates in the translation process, or a post-editor, who corrects errors and omissions in the machine-translated text. .
The machine translation system includes bilingual dictionaries equipped with the necessary grammatical information (morphological, syntactic and semantic), which ensure the transmission of equivalent, variant and transformational translation correspondences, explanatory and special thematic dictionaries, as well as algorithmic grammatical analysis tools that implement any of formal grammars adopted for automatic text processing.
The most common is the following sequence of formal operations, providing analysis and synthesis in a machine translation system:
· entering text and searching for input word forms in the input dictionary with accompanying morphological analysis, during which the belonging of a given word form to a specific lexeme is established. In the process of analysis, information related to other levels of organization of the language system can also be obtained from the form of a word.
· translation of idiomatic phrases, phraseological units or cliches of a given subject area, determination of the basic grammatical characteristics of input text elements, homography resolution, lexical analysis and translation of lexemes. Usually at this stage unambiguous words are separated from polysemantic ones, after which single-valued words are translated using lists of equivalents, and to translate polysemantic words, so-called contextual dictionaries are used, the dictionary entries of which are algorithms for querying the context for the presence/absence of contextual determinants of meaning.
· Final grammatical analysis, during which the necessary grammatical information is determined taking into account the data of the target language.
· Synthesis of output word forms and sentences as a whole in the target language.
Analysis and synthesis can be carried out both phrase by phrase and for the entire text entered into the computer memory; in the latter case, the translation algorithm provides for the identification of so-called anaphoric connections.
Machine translation quality depends on:
· volume of dictionaries,
· the amount of information attributed to lexical units,
· thoroughness in compiling and checking the operation of analysis and synthesis algorithms,
· software efficiency.
However, none of the programs can yet be expected to provide a “correct” literary translation of a text consisting of complex phrases.
Modern hardware and software allow the use of large dictionaries containing detailed grammatical information. Information can be presented as follows: declarative(descriptive) and procedural(taking into account the needs of the algorithm) form.
Improving machine translation programs is related to the concept of soft text comprehension, according to which different users extract their information and their individual meaning from the same text. Model of soft text comprehension consists in the ability to generate different meaningful interpretations of the original object depending on different conditions and components of its perception.
More private "machines" to help the translator and editor - these are automatic dictionaries and terminological databases, computer thesauruses, screen editing tools, systems for spelling, terminology and grammatical correction of texts.
Modern machine translation should be distinguished from the use of computers to assist human translators. In the latter case we mean automatic dictionary, which helps a person quickly select the desired translation equivalent. Although in both cases the computer works together with a person (translator or editor), the content of the term “machine translation” includes the idea that the main part of the work of translating and finding translation equivalents and translation correspondences is carried out by the machine. themselves, leaving the person only to control and correct mistakes.
Computer dictionary to help a person - this is an aid for quickly finding translation matches; At the same time, in such dictionaries, some functions inherent in machine translation systems can be implemented to a limited extent.
IN information technology vary 2 main approaches to machine translation:
· superficial familiarization with the contents of a document in an unfamiliar language
· use of machine translation instead of the usual “human” one. This involves careful editing and customization of the translation system for a specific subject area.
The completeness of the dictionary, its focus on the content and set of linguistic means of the translated texts, the effectiveness of methods for resolving lexical ambiguity, the effectiveness of algorithms for extracting grammatical information, finding translation correspondences and synthesis algorithms play a role here.
As a type of language activity translation affects all levels of language - from recognizing graphemes (and phonemes when translating oral speech) to conveying the meaning of statements and text. In addition, machine translation provides the opportunity to test theoretical hypotheses about the structure of certain language levels and the effectiveness of the proposed algorithms.
Need for improvement machine translation is constantly increasing, since this is the most important condition for ensuring interlingual communication, the volume of which is increasing every year.
Other ways to overcome language barriers to communication - development or adoption single language, as well as learning foreign languages, cannot compare with translation in terms of efficiency.
Date of birth machine translation as a research field is generally considered March 1947; It was then that cryptography specialist Warren Weaver, in his letter to Norbert Wiener, first posed the problem of machine translation, comparing it with the problem of decryption.
Deals with machine translation problems computational linguistics, which was born in January 1954, when the world's first public experiment in machine translation was conducted at Georgetown University (USA). At the same time, under the leadership of the outstanding mathematician and cybernetics Alexei Lyapunov, active work on machine translation and in Moscow. At the beginning of 1956 at the Institute applied mathematics(IPM) named after M.V. Keldysh, the first domestic machine translation system from French into Russian began working.
Leaders among modern programs machine translation in Russia - the PROMT system (developed by the PROMT company, www.e-promt.ru) and the SOKRAT system (developed by the Arsenal company, www.ars.ru).
IN latest version PROMT has a fundamentally new functionality, “Associated Memory”. The “Associated Memory” mechanism allows you to train the system. With its help, you can save a text translation that satisfies you in the knowledge base and later use its fragments when translating similar texts.
SOCRATES tries to find an unambiguous solution and does not give variations in terms: a word that is not in the dictionary remains in its original spelling. PROMT usually offers several translation options for words and phrases.
Machine translation, which has gone through several stages of development, is currently focused on the idea of modeling the actions of a human translator. The translation process is very difficult, and proper use of the software's advantages largely determines the quality of the translation. Modern machine translation systems include many additional dictionaries. Based on the features of architectural solutions for linguistic algorithms, systems are divided into two types - “Transfer” and “Interlingua”. Automatic translation programs are built in accordance with this division. So, for example, the “Socrates” program translates much better than, say, “Magic Guddi” because the linguistic support of the first program is much stronger, and the dictionaries are much larger in volume.
Machine translation results always have to be edited. For example, the Pars program provides a function for additionally connecting dictionaries on various topics. After all, the quality of the translation produced by the machine also depends on the quality of the software. But even fine tuning The system for the vocabulary of the translated text does not take into account all its features, therefore translated words that have several synonyms are marked with an asterisk or are given in brackets as an option.
Internet technologies gave new development to machine translation and helped bring it to a new stage of development. Machine translation is an effective tool for viewing and searching for information in a foreign language, and this function is the main one when working on the Internet. The current state of machine translation allows us to obtain relatively correct text translations of web pages from most languages. Although fully automatic, high-quality translation is not possible, software is already available that makes the translation process easier.
As a result of customization to the subject area and integration with other document processing programs, machine translation allows you to automate the production of translated text.
The main problem All machine translation programs require the correct selection of thematic dictionary, as well as the construction of auxiliary dictionaries.
Translation partly depends on the level of training of the user (knowledge of the language, skills in working with programs, sense of language), and also to a greater extent on his ability to correctly work with a text editor, auxiliary utilities, dictionaries and phraseological reference books. Options for translations made with the connection of thematic dictionaries are provided by a good translation, the correct choice of the meaning of the word and the use of phrases in the text. This is explained by the fact that the machine configures its dictionary to select those synonyms that would be more consistent with the topic of the input language, and would translate in accordance with the topic of the output language.
2 approaches to the problem of machine translation development:
· installation on the use of a universal language of meaning, a direct approach to translation, transformation of the original text into the target text
installation on an intermediate language, modeling human language proficiency
The problem is that the meaning of a text in natural language depends not only on the sentence itself, but also on the context, which is associated with the polysemy of words and syntactic constructions, the practical impossibility of a global description of the semantic structure of the world even in a limited subject area, the lack of effective formal methods for describing linguistic patterns.
Unsolved problems machine translation is
· resolving the ambiguity of formal syntactic analysis of isolated text sentences
· overcoming the structural and semantic incompleteness of sections (fragments) of the text
· organization of flexible connection of different subject areas
· the need to understand the text as a whole entity
Machine translation programs are better at processing scientific, technical and educational texts that are characterized by a strict presentation of the material.
Conversational and journalistic style, where there are many specific phrases, but most words are used in literally, are suitable for evaluation translation, but manual editing is required to obtain a literate output text. The resulting translation is a kind of introductory text, where only the general thematic focus of the text is conveyed.
Translation fiction and poetry does not meet the requirements of the machine. The meaning of a text based on allegorical expressions is distorted during machine translation and is inaccessible even for review. The machine does not understand polysemy, which in turn leads to an incorrect interpretation of the translated text, which turns into nonsense.
You can try to minimize such misunderstandings by observing following rules:
· correctly build thematic dictionaries
· check the original text at the stage of pre-preparation of its translation
· edit at the final stage of translation
· use dictionary programs correctly
· good knowledge of grammar and vocabulary, as well as the subject of the source text
· use vocabulary, clichés and word forms correctly
· timely update special dictionaries with new terms
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