Preserving linguistic and cultural heritage of the Tuvan ethnos in the digital era; [Сохранение языкового и культурного наследия тувинского этноса в цифровую эпоху]

This article presents an analysis of effective strategies for preserving and studying the Tuvan language through the application of methods and technologies such as corpus linguistics, artificial intelligence, and crowdsourcing. The paper examines the development process of educational and communicative applications utilizing neural networks, as well as the integration of language community-created projects into national initiatives for preserving and developing the languages of Russia’s ethnic groups. The study investigates the digital presence of Tuvan culture and language in generative artificial intelligence systems, including experiments with large language models (GPT-4, Google Gemini, Claude AI) and multimodal technologies, which demonstrated varying levels of representation. The authors also conduct a SWOT analysis of Tuvan linguistic and cultural heritage in the digital age, identifying strengths such as automated material processing and new archival capabilities, as well as weaknesses, threats, and opportunities associated with technological developments and human factors. The primary conclusion, based on positive trends, suggests that combining traditional methods with cutting-edge technologies can play a crucial role in preserving Tuvan language and culture for future generations. © 2024 Ch. K. Lamazhaa. All rights reserved.

Авторы
Novikova M.L. , Novikov P.N.
Издательство
Ламажаа Чимиза Кудер-ооловна
Номер выпуска
4
Язык
Русский
Страницы
173-187
Статус
Опубликовано
Год
2024
Организации
  • 1 Russian Language and Cultural Studies Department, Russian Language Institute, RUDN University, 10, bldg. 3 Miklukho-Maklaya St., Moscow, 117198, Russian Federation
  • 2 Law Institute Department of Foreign Languages, RUDN University, 6 Miklukho-Maklaya St., Moscow, 117198, Russian Federation
Ключевые слова
artificial intelligence; digital presence; language model; machine learning; machine translation; neural network; Tuvan language
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