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Chukwuemeka Odumegwu Ojukwu University
Anambra State

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Communicating the Dynamics of AI and Nigerian Language Studies: The Izon Language in Perspective


Title: Communicating the Dynamics of AI and Nigerian Language Studies: The Izon Language in Perspective
Author(s): Preye Samuel OBRIKI & Timothy Ekeledirichukwu ONYEJELEM
Abstract: Artificial Intelligence (AI) has the requisite potential to positively impact the study of indigenous languages in Nigeria by facilitating their preservation, revitalisation, and accessibility through digital tools. Despite Nigeria's linguistic diversity, the Izon language faces a foreseeable danger of extinction due to language shift, nonpreservation by native speakers, and a lack of modern digital documentation. There is a critical need to investigate how AI-driven platforms can bridge the gap between traditional oral heritage and modern digital archiving. It is against this backdrop that the current study examined the application of AI in preserving the Izon language and investigated various digital platforms for archiving natural languages. The study adopted the Technology Acceptance Model (TAM) and the Digital Generative Multimedia Tool Theory (DGMTT) in explaining how traditional methods of language preservation are failing to keep pace with the digital migration of global communication. A descriptive research design was employed, using qualitative methods to collect data from ten selected digital platforms and forty native Izon speakers. Findings revealed that AI-based platforms significantly improve the learning and speaking of Izon and offer robust frameworks for digital archiving. However, the study also noted that lack of ICT literacy and high costs are significant barriers. The study concluded that engaging AI is essential for the survival of the Izon language in the digital age. This research bridges Nigerian linguistics with advanced AI theory, offering a model for indigenous language survival. The study identified that previous studies have focused on AI in major world languages, leaving minority languages behind. This work therefore addresses the scarcity of research regarding AI's interface with minority Nigerian languages like Izon. Based on the findings, the authors recommended that earning institutions in the Niger Delta should integrate AI tools into their curricula; and governments should formulate policies to bridge the digital divide.
Keywords: AI, Language preservation, Language shift, Digital archiving, Izon Language learning, DGMTT.

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