Automatic Extraction of Handshapes Inventory in Russian Sign Language
Development of an inclusive society challenges researchers to study
representatives of various social groups, including those with unique
cognitive and communicative characteristics. One of these groups is the
deaf and hard of hearing, which differs significantly from other people with
disabilities in cultural and linguistic aspects. This article deals with the
difficulties that sociologists face interviewing the deaf and hard of hearing.
The authors consider the main cognitive and communicative features of this
group that influence the course of questioning, the role of sign language
in the perception of a sociological survey (including in writing form),
analyze the specifics of question-and-answer communication with deaf
respondents, which consists, first of all, of a difficult semantic and contextual
understanding of questions. The authors also describe the specifics of
information perception by respondents with hearing impairments using
specific examples from the researcher practice. Based on expert interviews
and methodological reflections on the results of several empirical studies,
the authors suggest possible ways to improve the quality of communication
between the hearing researcher and the deaf respondent, as well as increase
the validity of the data obtained during the survey.
The article proposes an analysis of three semantic fields in Russian Sign Language (RSL): ‘thick’, ‘thin’ and ‘pointed’. These fields are covered in RSL with a particular group of signs, namely, size and shape specifiers (SASSes). The paper describes features of SASSes in other sign languages, known from previous research, and proposes an analysis of these signs in RSL based on a detailed study of their contexts. Particularly, the article argues for distinguishing two types of components in these signs (specified and non-specified ones), discusses the semantics of non-manual markers and describes two morphological forms of SASSes.
Sign languages are the main way for people from deaf community to communicate with other people. In this paper, we have compared several real-time sign language dactyl recognition systems using deep convolutional neural networks. Our system is able to recognize words from natural language gestured using signs for each letter. We evaluate our approach on American (ASL) and Russian (RSL) sign languages. For ASL, we trained on dataset prepared by Massey University, Institute of Information and Mathematical Sciences, for RSL we collect our own dataset, which we aim to enlarge together with RSL community in Russia. The results showed 100% accuracy for ASL Massey dataset, while RSL recognition quality is behind sufficient quality due to much more complex nature of real-world RSL dataset.
In this paper, we compare several real-time sign language dactyl recognition systems and present a new model based on deep convolutional neural networks. These systems are able to recognize Russian alphabet letters presented as static signs in Russian Sign language used by people from deaf community. In such an approach, we recognize words from Russian natural language presented by consequent hand gestures of each letter. We evaluate our approach on Russian (RSL) sign language, for which we collect our own dataset and evaluate dactyl recognition.
Sign language is the main way to communicate for people from deaf community. However, common people mostly do not know sign language. In this paper, we overview several real-time sign language dactyl recognition systems using deep convolutional neural networks. These systems are able to recognize dactylized words gestured by signs for each letter. We evaluate our approach on American (ASL) and Russian (RSL) sign languages. This solution may help fasten the process of communication for deaf people. On the contrary, we also present the algorithm for generating sign animation from text information using text-to-sign video vocabulary, which helps to integrate sign language in dubbed TV and combining with speech recognition tool provide full translation from natural language to sign language.
The paper is focused on the study of reaction of italian literature critics on the publication of the Boris Pasternak's novel "Doctor Jivago". The analysys of the book ""Doctor Jivago", Pasternak, 1958, Italy" (published in Russian language in "Reka vremen", 2012, in Moscow) is given. The papers of italian writers, critics and historians of literature, who reacted immediately upon the publication of the novel (A. Moravia, I. Calvino, F.Fortini, C. Cassola, C. Salinari ecc.) are studied and analised.
In the article the patterns of the realization of emotional utterances in dialogic and monologic speech are described. The author pays special attention to the characteristic features of the speech of a speaker feeling psychic tension and to the compositional-pragmatic peculiarities of dialogic and monologic text.