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The article attempts to summarize materials on the study of Russian sign language: as a result of analysis of materials from scientific and lexicographic sources, the main problems of studying and describing the main means of communication for deaf and hard of hearing citizens of the Russian Federation are formulated, the degree of research of Russian sign language is analyzed, and the prospects for this current area of modern linguistics are determined.

For the first time, the method of bioclimatic modeling was used to determine the boundaries of the range of occurrence of a potential polemochoral species Avenella flexuosa (L.) Drejer. The simulation was performed by the method of maximum entropy (MaxEnt). It is shown that the conditions for the growth of this species are initially suitable (the probability of finding 0.54 and higher) in the territory of Central Russia. For comparison, the same bioclimatic modeling approach was applied for the occurrence data of Carex brizoides L. species, the polemochoral origin of which is not in doubt. It is shown that its growing places are beyond the limits of the climatic optimum (the probability of finding 0.08) in the territory of Central Russia.

Erkul, Karaman ( Aksaray, Yazar ), Bucklandiella subsecunda (Harv.) Bedn.-Ochyra & Ochyra Contributor. R. Ochyra Madagascar. Diana Region, Tsaratanana Massif, 14° 01′ S, 48°56′ W, 1200–2400 m a.s.l., April 1924, leg. Perrier de la Bathe s.n. (H-Brotherus, JE-Herzog, PCP.de la Varde 0707821, PC-Thériot 0708099). Racomitrium Brid., in its traditional circumscription is poorly represented in the moss flora of Madagascar and hitherto only one specimen of this genus has been discovered on this fourth largest island in the world. It was collected in 1924 by Perrier de la Bathie on the Tsaratanana Massif, and Thériot (1926) reported it as an unnamed form of Racomitrium lepervanchei Besch., a species endemic to Réunion Island. As Racomitrium proved to be heterogeneous, it was split into six segregates (Ochyra, Żarnowiec et al. 2003; Bednarek-Ochyra, Ochyra, Sawicki et al. 2014; Bednarek-Ochyra, Sawicki, Ochyra, et al. 2015; Sawicki et al. 2015), R. lepervanchei was placed in the genus Bucklandiella Roiv. Nevertheless, the voucher specimen was not studied by De Sloover (1977) in his survey of African Racomitrium and this material was assigned either to R. crispulum (Hook.f. & Wilson) Wilson (Crosby et al. 1983) or Bucklandiella membranacea (Mitt.) Bedn.-Ochyra & Ochyra (Marline et al. 2012), as R. lepervanchei was considered to be conspecific with these species (Clifford 1955; Lawton 1973). The specimen from the Tsaratanana Massif has distinct auricles and broad, flattened costa with 6–8 enlarged ventral guide cells, which are typical of Bucklandiella subsecunda. This is a pantropical oreophyte, widespread in tropical and subtropical Asia (Frisvoll 1988), subSaharan Africa (Bednarek-Ochyra and Ochyra 2012a, 2013; Ochyra and van Rooy 2013), Central and South America (Bednarek-Ochyra et al. 1999; Bednarek-Ochyra and Ochyra 2012b; Ellis, Bakalin et al. 2013) and the maritime Antarctic (Ochyra, Lewis Smith et al. 2008).

The paper analyses current computer Sign Language translation systems. Their advantages and disadvantages are detected. The main drawback is the lack of original text semantic analysis module capable of solving the task of disambiguation. A general scheme of translation system from phonic Russian to Russian Sign language including a module for semantic analysis is presented. It includes a block of source code analysis, developed by the authors, responsible for handling the semantic component of the Russian language. The semantic module relies on Tuzov’s dictionary. The semantic analysis algorithm is also described. The text analysis is completed when each word gets only one semantic description thus solving the problem of ambiguity. The most important developments of the semantic analysis module include the following: expanded collection of gestures, parsing of complex sentences, account in the algorithm analyses predicates classifier of Russian Sign Language. Testing of algorithm is made. The article compares the existing systems of computer translation from phonic to the sign language. The advantages and disadvantages of the considered systems are revealed and a conclusion is made about the need to take into account the semantic aspect of the translation process. A technology of semantic analysis is suggested. The model to choose an adequate meaning of a polysemic word or homonym on the basis of the automatic text processing system «Dialing» is described. Examples of the use of the software are given. The questions of testing the working capacity of the semantic analysis module are given due attention too. To enhance its efficiency, the system of semantic analysis was added to the translation system «Surdophone». To verify the efficiency of the semantic module’s operation, a comparison is made with the definition of some words’ semantic meanings by the systems «Yandex Translator» and «Google Translator». The present system showed its advantage in more complex cases. Also, the base of gestures of the RSL whose names are homonyms and polysemic words of the Russian language, were added and the features of their performance were revealed.

This work examines Russian sign language grammar peculiarities which should necessarily be taken into account in the development of a computer signer, making a literal adaptive translation from Russian audible (sounding) speech to Russian sign language. Detailed description of the Russian text analysis stage, including morphological, syntactic, and semantic analysis, is also given in the paper.

The paper considers peculiarities of the Russian sign language grammatical system which should be taken into account when developing a computer sign language translator. We draw a conclusion that the Russian sign language has its own grammatical system which includes word formation, morphology, and syntax, and may be described in terms and categories of the Russian language. The stage of the Russian text analysis, including morphological, syntactic, and semantic analysis, is characterized in detail.

The paper considers computer sign language translation technology for deaf people. A detailed characteristic of the Russian text analysis stage, including prior semantic and semantic interpretation within the framework of developing a program for Russian text computer sign language translator into colloquial Russian sign language is given. Problems arising at this stage are also emphasized. Peculiarities of the Russian sign language grammatical system necessary to take into account when developing a computer sign language translator are singled out.