THE LINGUOSEMIOTIC ASPECT OF THE "PICTURE ---- TEXT" COGNITIVE SYSTEM. Maya I. Otkupshikova, Valentina N. Ignatova firstname.lastname@example.org ABSTRACT : Consideration is being given to the elaboration of models for automatic synthesis of connected texts in natural (Russian) language in accordance with the linguosemiotic aspect. The models like these are directed toward making linguistic pro- cessors for the system which stimulate a person to under- stand our text. As for the systems they cannot be only sati- sfied with a grammatical level of the synthesis. The seman- tics in the broad sense of the word must be taken into acco- unt by them. Our models are the basis of the linguistic pro- cessor for the AI "picture --- text" system. Let us consider models of the systems for modelling the personal speech behaviour according to the linguosemiotic aspect. The models for reproducing specific types of the personal speech behaviour (speech activity) are cybernetic models. Generalization to the speech behaviour can be reduced to three types as follows: 1. In the course of human activity the personal speech behaviour [when the textual production and comprehension (perception) take place and as a result the wanted actions are made] is accumulated or information is given for subsequent activity, management of different personal activities is responsibility of them and so on, i.e. the usual communication is run; 2. The speech behaviour of the translator from a foreign language to a native one and vice versa; 3. The speech activity in studies of native or unnative languages, a certain field of knowledge, profession and so on. The types listed above differ from one another by purposes, initial data and results. The difference is based on producing different cybernetic models of the speech behaviour (compare to expert systems of automatic translations, information systems of different types, tutorial systems). The basis for the different types of speech activity is something in common, otherwise the communication between members of the same language group would not be possible. First of all the common consists in a mechanism of linguistic community (or as it is usually said in the language system). Because of this to solve problems in modelling requires a general theory with explicative intensity for aspects of both the structure of the linguistic mechanism and regularities of its functions. It is well known the generation of such suitable theory for all modelling problems seems to be very difficult. And objectivity of the difficulty consists of the fact that the language as the linguistic mechanism is a typical example of cybernetic "black box". It is really in existence and it functions efficiently but members of the communication are not given it in the immediate perception. They know only what is available at entry and at the output of the "black box". So roughly speaking the author knows the true sense of the text that he wants to communicate the receiver (entry) by means of the given text (output). On the other hand in case of the perception the receiver is given the text for interpreting its sense. We cannot immediately observe the language organization and function (the linguistic mechanism), among other things, because of the fact that there is a great body of linguistic theories, hypotheses and points of view which are not specific to so-called natural sciences. The second problem relating to the first one consists in complications and polyaspected formations of the linguistic system taking into account all aspects of automatic systems for speech corpora. Such limitations are essential and for the "picture --- text" system as well. The second aspect of the community for all types of the speech behaviour consists in general semiotic nature of linguistic signs which are characterized for speech corpora (texts), they provide indispensable components of the speech behaviour and therefore components of models for the speech behaviour. As is known, for describing semiotic nature of linguistic signs they use a simple model - so-called Frege-Ostgoff triangle - its angles represent denotative, significative and verbal aspects of the linguistic sign, as for sides they represent connections of these aspects. Of great importance is the direction of the connections, i.e. to find "a way". For our further purposes two "ways" must significantly be kept in mind: denotat - significat - verbum and verbum - significat - denotat. These "ways" model the cognitive process, the process of knowledge as if it be. Being so simple the model is quite strong to explain the semiotic nature of the language. It should only be added a variety of arguments. Practically "the triangle of significance" is used to explain a simple linguistic sign conforming very often to a word and not so often to a combination of words, i.e. elements which may be given by final or conditionally final lists. At the same time any type of the personal speech behaviour and any type of models for the speech behaviour, correspondingly, are concerned not only with insulated signs of the finite alphabet but with different combinations of them and in practice they may infinitely be reproduced in connected texts. Thus we have to show that speech corpora (texts) posess qualities of liguistic signs and they may semiotically be interpreted by above - mentioned devices. [The position that the text has status of the linguistic sign (it is a main linguistic sign, complex sign) is approved by a lot of linguists (Dressler, Hartmann, Moskalskaya, Serkova and so on) while a humber of linguists (Emile Benveniste, Zvegintsev) deny the sign nature of the text. In spite of the community of the sign nature of both the natural language and artificial languages it might be well point out the specific character as follows: the linguistic sign has three- and not two- way - character (denotat, significat, word); the linguistic sign is characterized by combinations with other signs of the same rank (certain artificial languages have the same features). So combinations of linguistic sings produce complex structural and semantic unities - sentences and texts - they decrease or lose a number of features of the simple linguistic sign and preserve the main features: three-way character, linearity, arbitrariness. And sentences decrease (texts completely lose) both the feature of reproduction in combinations and the feature of assymmetry between "significative" and "signified" that is changed according to the following regularity: the more complex sign, the less than probable the feature of assymmetry for it. Thus speech corpora are complex linguistic signs which can be described by means of the correlation: the denotative aspect - the significative aspect - the verbal aspect, that is arranged in the known triangle. It is evident the triplicity of the linguistic sign is considered to some degree in all types of cybernetic systems for the speech behaviour. And taking into account correlations of verbal and significative aspects of the speech corpus it obviously is the condition that should be made to produce the cybernetic system with high success. The quest for ignoring the significative aspect is only capable of revealing possibilities of formal features of words, establishing their relations with other words of the sentence in the initial stages of analyses for input texts. As for synthesis of the texts, on the whole the sense (the signivicative aspect) is an entry for its realization. The third denotative aspect is certainly neglected by the most of projected cybertenic systems but it is obvious that except for learning the system of concepts (translating from one language to another, for example) it is essential to have a knowledge of the world this system described. The denotative aspect (in other terminology it is the referencial aspect) became to take into account of the AI expert and other systems including cognitive systems. The cognitive aspect of the speech activity is an essential component of it. There are, for example, answers to tasks of the school teacher: "Очъъичтупе, бпм аь аудейу лч ыиъияоъуу" ("Tell me, please, what did you see on the excursion") or "Нмъпомхпе ъазцльх очъъичц нм дчллмкя оуъялия" ("Tell me a connected story about the given picture"). The way for producing the speech corpus takes place: the denotative aspect - the significative aspect - the verbal aspect (the text). Another way is characterized by many systems for teaching, translating, reading belles - lettres and scientific works: the verbal aspect - the denotative aspect - the significative aspect. These two main types of knowledge form the basis for the human activity and existence, and both are connected with knowing realities of our world. The "picture --- text" system models the first type representing the cognitive intellectual system. As the denotat we have scenes describing certain situations. The experimental variant of the system dealt with situations describing outdoor scenes with objects like "беймаеи" ("a man"), "дмк" ("a house"), "ейщ" ("a fir"), "йунч" ("a lime"), "жояцмауи" ("a truck"), "йежимачз кчэулч" ("a car"), "аеймъунед" ("a bicycle"), "эйзнч" ("a hat"), "ймнчпч" ("a spade"), etc. Every object has a number according to its standard and a referencial index that is an indication of the object number among other objects with the same standard. As the collection of relations the following binary space relations of objects were employed: "лчд" ("above"), "нмд" ("under"), "цч" ("behind"), "неоед" ("in front of"), "оздмк" ("near"), "ъйеач" ("to the left of"), "ъночач" ("to the right of"). In this case specific features of the denotat are evident: these are not real scenes which might be observed in the street but some sort of imitation of the similar scenes is constructed by a person and drawn with the use of a computer. The picture is constructed by the simplest graphics editor (needless to say that we don't bring forth problems for analyses of arbitrary pictures with an "intricate" entry and a process of object understanding). At present the editor allows for drawing objects from the fixed collection on the display space that is chosen by a user. In future it is assumed to provide a means for a new-object entry by the user oneself (and the user will be required a name of the new-object entry and descriptions of grammatical features of the name). Because of working the graphics editor in the system there are many objects of the scene constructed and every object is characterized by co-ordinates of its own. Thus we are not concerned with the real world but with the world that is artificially constructed and reflected both real objects and real space relations though mediately. So the specific character of speech corpora is like that and the speech corpora can reflect and describe not only the real world. Thus the specific character can be discovered in a broad understanding the reality that contains not only the whole physical world round us but intellectual, social, inner worlds of human being, everything that was created by people including speech corpora themselves as well as unlimited abilities for describing real systems equally with unreal systems according to extended terminology: possible, thinkable, probable, fictitious, problematic worlds. This ability is realized, for instance, by fairy-tales, mythes, fantastic tales as well as belles-lettres works which mediately reflect the real world through typified images and often by means of fabricated topics and characters. In such a manner the problem is to define the type of the selected world and to act according to the choice. The next stage of the cognitive process is an organization of the scene content. [It is evident that natural situations of the world (scene) description don't contain the distinctive division of stages: significative and verbal aspects closely interact with each other but as it takes really place the investigators can only put forward more or less convincing hypothesis because it is impossible to interpret it in a large measure]. For describing the scene content we take the method of semantics representation that can recently be obtained by the works about precise descriptions of the language for automatic problems. The method of semantics representation has the appearance of objective-predicative structures. In our case the predicates identify different space relations of objects. It should be distinguished binary relations which indicate correlations of two different objects and unary relations which point at the object positioning in the particular scene with respect to a coordinate system. Results for the process of the scene analyzing can be represented as a list of objects "participating" in the situation and a set M of triplets like xRy where x and y are objects in the given scene. The set M is constructed so that every pair of objects "participating" in the situation is given all relations which link objects in the situation, i.e.: the set M fixes the whole information about the scene that is essential for our further work. In the system knowledge about the scene is given as a table where the entry is an ordered pair of the scene objects and the result is a set of space relations linked these objects. The list of studied relations is fixed. Thus the process of the transition from the picture to the text has two stages: 1. The picture analysis for constructing the table. 2. The text synthesis according to the constructed table. The first stage models perception and interpretation of the scene by a person (the way from the denotative aspect to the significative aspect). The second stage models speech abilities of a person to speak about the perceived and interpreted scene (the way from the significative aspect to the verbal aspect). In natural situation, i.e. when a person describes the scene, it is possible to have the text variants with the different sequence of objects in the text, the different choices of the initial object for describing the scene, the different structures of the actual segmentation of the text. For the "picture --- text" model (the model always consists of generalized and so simplified descriptions of objects from life) we select a certain method to generate the scene content and the method determines a certain construction of the given text. Requirements on the given text are as follows. Every sentence of the text conforms to the statement about a connection of one object to another. As this takes place, every sentence introduces a new object through the object already introduced. Moreover at the start of the text there is a sentence introducing the object independently of other objects. The mechanism of text-generation like this gives a rather good approximation and obtainable texts can be considered as a reasonable description of the scene observed. Realization of the method of text-generation dictates some rules of the choice from the set M of elements for the resulting sequence S and the rules for ordering these elements as well. To construct the sequence like this it is necessary to define the rules for the choice of the specific subset from the set M. With this in mind it is essential for every object except one to define the only triplet where the object takes the position of the left member. The procedure for selecting the sequence S, i.e. to select "the content" from the set M, constructs a content graph, according to it the text is synthesized. When synthesizing there is a number of unique manipulations: -selection of the verb designated as a unary predicate according to the object type, for example, "Нйьаеп мюйчим", "Ъаепуп ъмйлфе"; -introduction of ranks for objects and relations which define their importance or intimate connection with objects, correspondingly; - introduction of definitions for some triplets xRy, a type of "эйзнч ЛЧД у ОЗДМК ъ беймаеимк" ---- "беймаеи а эйзне"; - assignment of referencial indices; - generation of new objects, for example, "аеймъунедуъп". But both the mechanism for distribution of text elements (the actual segmentation) and the mechanism of the sense repetition have special linguistic characters, the scheme demonstrates their work for generating connected texts. Connectivity of any text just as the natural text and so the artificial one (if it is called upon to imitate the natural text) follows four kinds of conditions which directly involve the sense structure of the text: conditions of the sense repetition; conditions of the sense prediction; conditions of the sense distribution in the text and logical relations of the text parts. The sense distribution plays a distinctive role, i.e. it is a composition of the text information. The actual segmentation, being a fundamental category of the text composition, provides the sense distribuition that in turn is responsible for the text connectivity. As any text phenomenon the actual segmentation is represented by sentences of the text. Elements of the actual segmentation are theme and rheme, they are not in accordance with syntactic units. The theme is an element of the sentence for connecting with earlier contexts; the rheme can be defined as a main purpose of the communication within the limits of the sentence, it consists in reporting a receiver unknown and/or essential information (from author's point of view), at the same time the rheme is an element of the sentence that has potential connections with following contexts. Themo-rhemic structures of different degrees of complication functionate in the texts. Fundamental elementary structures are as follows: a) the canonic structure of "close connection". Schematically it is represented like this: the theme1 - the rheme1; the theme2 (of equal idea to the rheme1) - the rheme2; the theme3 (= the rheme2) - the rheme3 and so on. For example, "Аляи ноуесчй и ючюяэие. Млч неийч нуомжу. Нуомжу юьйу аияълье". [For comparision with the "picture-text" system: "Очъпеп деоеам. Неоед деоеамк ъпмуп ъичкехич. Лч ъичкехие ъудуп беймаеи".] As a modification of the "close connection" structure may be thought of the structure that is produced by means of the quantifier word as plurality with the first rheme: the theme1 - "клмжм" (the rheme1); the theme2 ("мдул уц") the rheme2; the theme3 (= "дояжмх уц" the rheme1) - the rheme3 and so on. "Я ъпчоуич юьйм леъимйщим юочпщеа. Неоаьх юочп юьй юецдепел. Я апмомжм юочпч юьйу ъьл у дмбщ". [For comparision with the system: "Очъпяп нзпщ йун. Неоед неоамх йунмх ъпмуп жояцмауи. Неоед апмомх йунмх ъпмуп беймаеи. Оздмк ъ поепщех йунмх лчсмдупъз неъмблуфч. Неоед бепаеопмх йунмх ъпмуп ъичкехич. Ночаее нзпмх йунь едеп аеймъунедуъп"]. b) the parallel structure: the theme1 - the rheme1; the theme1 - the rheme2; the theme1 - the rheme3 and so on. For example, "Кчйщбуи ужочй а ймэчдиу. Мл жомким иоубчй у ъкезйъз. Мл юьй ъбчъпйуа". [For comparision with the "picture- text" system: "Ъпмуп дмкуи. Дмкуи ъ цчюмомк. Дмкуи ъ пояюмх", converted by the system with automatic editing to "Ъпмуп дмкуи ъ цчюмомк у ъ пояюмх".] c) the reverse parallel structure which realizes relations between different themes and one and the same rheme: the theme1 - the rheme1; the theme2 - the rheme1; the theme3 - the rheme1 and so on. The construction is characteristic of not frequently found text instances of predicate substitution by means of special substitutes the type of: "пмте, пчи (те), дч, леп". "Юочп бупчй илужя. Ъеъпоч - пмте". [For comparison with the system: "Едеп аеймъунедуъп а эйзне. Едеп дояжмх аеймъунедуъп, пмте а эйзне" or "Удяп поу беймаеич. Ичтдьх уц лус а эйзне".] d) the "bunched" structure: the theme1 - the rheme1, the rheme2, the rheme3 ... These constructions are specific to a type, for example, of compositions with homogeneous predicates which can be believed to be separate sentences. "Мл нмэей дчйщэе нм яйуфе. Нмпмк цчаеоляй цч яжмй. Амэей а амомпч". And so on. In natural texts the given structures can be obviously used together with each other. The texts where only one structure of the actual segmentation is represented are rare and if they are long enough they can be interpreted as a little bit artificial but sufficiently understandable texts. As was shown above the "picture ---- text" system takes into account all types of the given structures (both in the pure state and in combination with each other) , , this fact enables to offer strong possibilities of the system and provides the texts synthesized not only compact but natural form (from language bearer's point of view). Let us consider an example of the text synthesized by the system: "Ъаепуп ъмйлфе. Нйьаяп дач мюйчич. Ъпмуп дмкуи ъ цчюмомк, а импмомк укеепъз ичйупич, у ъ пояюмх, уц импмомх удеп дьк. Лч цчюмое ъудзп дае нпубиу. Цч цчюмомк очъпяп дае ейиу. Неоед цчюмомк ъпмуп ъичкехич, лч импмомх ъудзп дач беймаеич. Мдул уц лус ъ илужмх, дояжмх а эйзне. Неоед дмкуимк удеп беймаеи, оздмк ъ импмоьк лчсмдупъз ъмючич. Ъночач мп дм- куич очъпяп нзпщ йун. Неоед неоамх йунмх лчсмдупъз жояцмауи ъ неъимк. Лч жояцмауие ъпмуп беймаеи ъ ймнчпмх. Оздмк ъ жояцмауимк лчсмдупъз иябч неъич. Неоед апмомх йунмх ъпмуп дояжмх беймаеи, пмте ъ ймнчпмх. Неоед поепщех йунмх лчсмдупъз неъмблуфч. Неоед бепаеопмх у нзпмх йунчку ъпм- уп дояжчз ъичкехич, лч импмомх йетуп беймаеи. Неоед ъичкехимх едяп дач аеймъунедуъпч. Ичтдьх уц лус а эйзне. Йепзп поу нпубиу." The text makes allowance for possibilities of the system almost without exceptions. We can see quite well using language mechanism of substitution with the sense repetition of the theme and the rheme. The substitution is realized by means of "which-word" constructions and above all it is possible to do "sticking" two simple sentences in a complicated sentence. It should be noted that the specific character of the actual segmentation in Russian [to be expressed by means of words, order (for neutral speech styles)] and the triadic composition of elements in the sentence (xRy) as well provide a means to carry out the first experiences without expansive morphologo - syntactical synthesis. In conclusion. In was necessary to look for well-known linguistic facts again because of the specific character of our problem, i.e. cognitive-graphical approach and desire to develop and use hyper-text technologies that brought to unexpected but rather effective results and allowed us to move on making the linguistic processor for the AI "picture --- text" system. Similar systems can be applied to various domains (including teaching fo-reign languages), facing the problem of drawing a scheme, a map, a plan and so on matching its textual description in natural language, in different robot controlling tasks and in some other applications. 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