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V. Iaroslavski CREATIVE SEARCH OF THE HOMOGENEOUS TEXTS



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V. Iaroslavski CREATIVE SEARCH OF THE HOMOGENEOUS TEXTS

On the base of special course "Statistical methods in linguistics" studied on Mathematics and mechanics faculty of Saint-Petersburg State University the program to verify of homogeneous texts hypothesis was created by the author. This program was written in Pascal language (ver. 7.01) with the object-oriented library Turbo Vision which is for high effect implementation of program interface and advanced help system for users. Another version is written in Java language. Theoretical part of this verification is based on Xi-2 criterion [1]. The suggested hypothesis is that probabilities of appearanced same rhythmical words for the different prosaic texts are equal.

User can verify the hypothesis by the comparison of frequencies of rhythmical words or by suggested probabilities of it. The initial marked text should be written in a file of ASCII format. So, the input of program is a rhythmical text. The text is marked by the divider of words (symbol "|") and the symbol "<" which is used to set an accent. The foreign words are available. All results of the analysis are output in new files. Words with identical rhythmical structure for convenient are written in the separate files with the information about its location in source text. Relative and absolute frequencies of rhythmical words and Xi-2 value are output too.

This program can be used by the students learned the special course "Statistical methods in linguistics" as a manual.



References

  1. Donald E. Knuth. The art of computer programming. Volume 2. Seminumeral Algorithms. — Addison-Wesley, 1969.


A.Smolsky GLOTTOLOGICAL MODEL OF PHONEMEGRAPHIC LANGUAGE LEXICAL UNIT

Notion as a main category of epistemology reflects the fundamental role of this entity corresponding to some phenomenon or object of reality for storing, transferring and processing of information. In many natural languages the item "notio" is often identical to the item "lexeme" which is used for definition of lexical unit appearing as elementary part of vocabulary. Knowledge engineering with possibilities of notion interaction is an important direction in development of expert systems and computer-assisted instruction tools. It assumes the creation of appropriating algorithmic procedures and unified dictionaries of natural languages.

Construction of some language electronic dictionary considered as a part of common knowledge base rely on mathematical model of lexical unit (notion). Generally, two kinds of notion model are used in philology: linguistic and encyclopedic. Linguistic model considers phonetical, graphical, lexical, orthographical, morphological and derivative aspects of speech components. Encyclopedic model is added by video and audio features of lexical units. Functioning of advanced artificial intelligence systems must be based on simulation both grammar-linguistic aspects of language vocabulary and informational nature of words and ways of their utilization. In this case the notion model must include not only audiophonetical, videographical, etymological and another parts of linguistic or encyclopedic model, but also structural, objective, subjective, context-sensitive, introductory and some other characteristics of language constants.

The notion model that maps properties of lexical units mentioned above is called glottological model. It may be used in various inquiring, translating, teaching, testing, speaking, playing and some other kind of tools. On the base of this model may be created more complex models representing hierarchical system of all human knowledge. At present glottological model is used as a base of dictionaries and computer-aided procedures in CAI tool for play mode learning of foreign languages.




G.E.Kedrova, O.V.Dedova, E.L.Barhudarova, V.V.Potapov, E.B.Omeljanova RUSSIAN PHONETICS IN INTERNET: HYPERTEXTUAL MULTIMEDIA COURSE FOR DISTANCE EDUCATION



Abstract: This paper is about a hypertextual multimedia course in Russian phonetics. The course consists of several training modules (prepared by the authors) that are Russian vowel system, Russian consonant system, Russian intonation and Russian accentuation.

As is known Computational Linguistics is a very wide science which studies the language in different situations of its application, works on methods of developing language systems and language process and includes different directions. One of these directions is Applied Linguistics which develops methods of language teaching and especially those for new area of Distance, or Distributed, Education,. Distributed Learning can solve a lot of problems which education system is facing nowadays.

Teaching foreign languages distantly is possible and has big opportunities to grow fastly in the learning process. The main thing in distributed learning is not the technical tools which make the computer distance learning possible, but the development of methodic of distributed learning/teaching and effective organization of course materials.

However, automated teaching, especially computer linguistic didactics as a theoretical discipline, emerged much earlier; in Russia the first attempts to use modern computer technologies in language teaching (the overwhelming majority of the original works were devoted to the process of teaching Russian as a foreign language) were undertaken by the authors in the middle 80-s. Nevertheless, Russian language teaching sites still have many negative features[1]. From our point of view, the problem lacks prepared special teaching material as well as worked out methods of interactive strategies for postponed in time and /or distance education [2]. Moreover, there is no acceptable solution for the problem testing and automatic control of the process of acquiring knowledge and attainments.

The Interactive hypertextual multimedia course of Russian phonetics consists of several training modules, each of them is devoted to one of the following: Russian vowel system, Russian consonant system, Russian accentuation, intonation, and prosody. The introductory information module anticipates all the material concerning the general theory of speech production and speech perception. Each module has an auxiliary information part (glossary) in which you can find terms and basic concepts. All the modules of the course are linked to one another via cross-references and constitute one integral information complex. Basic concepts and statements presented in the course are supplemented by illustrations, sound examples, and exercises. The database that forms the basis of the course consists of: 1) detailed and exhausted description of the peculiarities of Russian sound system and accentuation; 2) animated cartoons of the articulation of Russian sounds that is based on X-ray photos of speech; 3) video recording of visible articulatory movements (first of all lips articulation); 4) sound files showing vowels and consonants as well as words in speech; 5) oscillographic pictures of sounds; 6) main stress patterns (for all parts of speech).

References

1. Dedova O.V., Kedrova G.E. K voprosu o didakticheskom materiale i metodicheskoy podderzhke distantsionnogo obucheniya russkomu yazyku v Internet. In: AATSEEL. Annual Meeting. Abstracts of papers. Toronto, 1997.

2. Dedova O.V., Kedrova G.E., Rudenko-Morgun O.I., Dunaeva L.A., Omelyanova E., Streltsova T. Kompyuter i yazykovoe obuchenie v Rossii. In: Mezhd. konf. Internet. Obshchestvo. Lichnost (IOL-99). S.-Petersburg, 1999.



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