By 2026, automated sign language recognition has moved from research laboratories into applied domains, including mobile translators, educational software and inclusive services. For Russian Sign Language (RSL), however, this field remains fragmented and is rarely addressed from a linguistic perspective. The aim of the article is threefold: to systematise the state of research on AI-based recognition of RSL with an explicitly linguistic frame; to identify the principal gap, namely the absence of a continuous parallel RSL-spoken Russian corpus; and to propose a concrete component-based architecture for an RSL-to-Russian translation system grounded in published evidence. The review focuses on seven blocks: the phonology, morphology and prosody of RSL; the gap between Russian and international corpora (BSL Corpus, DGS-Korpus, How2Sign, RWTH-PHOENIX-Weather versus the NSTU corpus and TheRuSLan); the evolution of AI architectures from HMM-based continuous recognition to transformer-based translation and large language models; the Russian landscape of datasets and systems built around Slovo, Bukva and Logos; the linguistic validity criteria for synthetic sign data; the mapping between Stokoe-style sign phonology and the outputs of real-time pose estimators; and the choice of a language model for the spoken-Russian decoder. The paper argues that a successful RSL-to-Russian (Sign-to-Text) system must couple linguistic knowledge - Stokoe phonology, predicate typology, mouthings and information structure - with engineering components in a principled way. In particular, it proposes a pipeline that combines RTMPose Whole-body as a real-time front-end, a Logos-pretrained vision encoder, a Vector Quantization sign tokenizer in the spirit of SignLLM and a language decoder from the GigaChat family. The contribution of the study is a literature-grounded synthesis of the state of the art with explicit identification of research lacunae and a justified component architecture for a target system.
In contemporary urban environments, public signage reflects not only language use but also broader processes of globalization, identity construction, and language commodification. This study investigates the linguistic landscape of Margonda Street, Depok, Indonesia, focusing on the representation of Indonesian, English, and other foreign languages in commercial signage. It aims to analyze how linguistic resources are displayed in urban commercial space and to identify the symbolic meanings and commercial values associated with their use. This study employed a mixed-methods case study design. Data consisted of 601 commercial signs documented through photographic observation and 40 semi-structured interviews with business owners or managers. Visual data were analyzed using the Linguistic Landscape framework, while interview data and field notes were examined through thematic analysis. The findings reveal that monolingual Indonesian signage remains the dominant form of commercial communication, followed by English, bilingual, multilingual, and hybrid signs. English was particularly visible in businesses associated with urban lifestyles, education, and services, whereas Japanese, Korean, and Arabic appeared in more specialized sectors. Interview findings indicate that language choice is influenced not only by communicative needs but also by symbolic and economic considerations. English is commonly associated with modernity, prestige, and global connectedness; Japanese with authenticity; Korean with popular culture; and Arabic with religious trust and legitimacy. The coexistence of these linguistic resources reflects a process of glocalization in which global and local influences are negotiated within a shared commercial environment. The study concludes that languages in commercial signage function simultaneously as communicative resources, symbolic capital, and economic assets. The linguistic landscape of Margonda Street demonstrates how foreign languages acquire commercial value while Indonesian continues to serve as a central marker of accessibility and local identity.
While Renaud Camus’ “Great Replacement” (GR) theory demonstrates the profound power of language to affect human behavior, it remains unclear how the text constructs a weaponized, imagined environment that actors mistake for their physical, perceived reality. The paper focuses on this ecolinguistic effect of GR discourse. Using methods of a systems approach and critical discourse analysis, we examine the English edition of You Will Not Replace Us! The aim of the study is to trace how the text becomes embedded within a specific cognitive ecology, rather than functioning as a statement about an external world. We establish that this ecological embeddedness is both operational - where the narrative becomes integrated into certain cognitive processes - and orientational, guiding its readers toward a specific type of environment. The findings show that Camus’ discourse provides both enablement and constraint for action in perceived and imagined environments. Regarding constraint, perception and imagination become bound by the zero-sum logic of a symbolic and metaphorical action - namely, replacement. Conversely, the cognitive enablers are four semiotic tendencies that structure verbal thought on an empirical level: tendencies toward repetition (“allness”), symmetry (imitation), identity (“sameness”), and stability (“stillness”). The narrative fulfills these tendencies by focusing on themes of pervasiveness, the loss and demise of values, the reversion of meaning, the separation of names and things, and an overarching sense of finality and determinism. Allowing for these four empirical “ways of meaning”, the narrative leads to cognitive entrapment. Consequently, GR adherents confuse their perceived environment with an imagined one.
Instrumental and integrative language attitudes play an important role in understanding the viability of languages. The present study investigates these attitudes among speakers of five titular languages of the Russian Federation (Ingush, Tatar, Tuvan, Chechen, and Yakut). This study aims to identify how age-related shifts in attitudes and usage impact language vitality within distinct sociolinguistic contexts. It investigates whether younger speakers of five autochthonous languages in the Russian Federation demonstrate patterns of language shift or language maintenance, focusing on the role of instrumental and integrative language attitudes across generations. Data were collected through a questionnaire survey and contextualized within the existing language ecologies, including societal, political, and institutional conditions. Contrary to expectations drawn from classical models of language shift, younger respondents (ages 18-25) displayed strong loyalty to their languages, actively using them in home and peer settings alongside Russian. These findings suggest that, in supportive sociolinguistic environments, youth can serve as active agents of language maintenance. Integrative attitudes were strong across all age groups, and Russian-titular language bilingualism is widely practiced, particularly in peer interactions, reflecting both symbolic attachment to autochthonous languages and the benefits of practical bilingual communication. Instrumental attitudes further revealed that languages were primarily maintained in culturally symbolic or informal contexts, while multilingual competence, including Russian and international languages, was valued for social mobility, particularly among younger cohorts. The research data also confirm that the respondents exhibit sustainable, ecologically conditioned patterns of bilingual practices. Overall, this study contributes to the sociolinguistic understanding of language use in multilingual contexts by revealing patterns of instrumental and integrative motivations across generations.
