
This article explores the growing role of digital technologies, social media, artificial intelligence, and online communities in the preservation and revitalization of endangered languages. It examines how platforms such as YouTube, podcasts, Facebook, Instagram, TikTok, Reddit, and Discord create interactive environments for language learning, cultural exchange, and community engagement. The article highlights the importance of AI-powered tools, speech recognition systems, virtual assistants, and chatbots in providing personalized language-learning experiences and improving learners’ pronunciation and fluency. In addition, the study discusses the contribution of digital language-learning applications, crowdsourcing platforms, and translation technologies to documenting and promoting endangered languages worldwide. Special attention is paid to the role of communities and language activists in raising awareness through online campaigns, hashtags, and collaborative projects. The article concludes that modern digital tools have become essential instruments in safeguarding linguistic diversity and ensuring the survival of endangered languages for future generations.
endangered languages, digital technologies, artificial intelligence, language preservation, social media, online communities, speech recognition, language learning applications, podcasts.
endangered languages, digital technologies, artificial intelligence, language preservation, social media, online communities, speech recognition, language learning applications, podcasts.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
