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Review Papers | Language Research | Volume 15 Issue 1, January 2026 | Pages: 1586 - 1596 | India
Preserving Linguistic Diversity: The Role of AI-based Language Learning Applications
Abstract: The frightening rate of language extinction suggests that around half of the world's 7,000 languages will disappear by the 21st century. This disaster can be addressed through the potential of Artificial Intelligence, provided the capabilities of AI-driven language learning applications are utilised appropriately. One such kind is demonstrated in this qualitative comparison study, wherein we assessed the efficacy of Duolingo and Memrise. The approaches include speech recognition, natural language processing, and adaptive learning, which are integrated into AI systems. Utilising secondary information, an analysis of the platforms, and a rigorous review of the literature, our research showed that these programs are proficient in enhancing vocabulary and alleviating learning obstacles; nonetheless, they are deficient in providing cultural experiences and real language. The study examines ethical problems, including data ownership, biased portrayal, and the divide between individuals engaged in the digital realm and those who are not. This paper presents a framework for ethically grounded, community-oriented AI development and offers practical recommendations for policymakers, technologists, and indigenous populations. It advances the discourse on equitable AI and linguistic diversity, enabling a global vision of an inclusive and dynamic digital future for language preservation.
Keywords: Language Preservation, AI in Education, Ethical AI, Digital Linguistic Diversity, Endangered Languages, Language Learning Applications, Duolingo, Memrise
How to Cite?: Amogh Shrivastava, Anand Zutshi, "Preserving Linguistic Diversity: The Role of AI-based Language Learning Applications", Volume 15 Issue 1, January 2026, International Journal of Science and Research (IJSR), Pages: 1586-1596, https://www.ijsr.net/getabstract.php?paperid=SR26116043049, DOI: https://dx.dx.doi.org/10.21275/SR26116043049