Examining AI Translation Errors in Igbo: Lexical Ambiguity, Misinterpretation, and Incorrect Word Substitutions Due to Contextual Deficiencies

  • Amaka Yvonne Okafor Department of Igbo & other Nigerian languages, Nwafor Orizu College of Education, Nsugbe, Anambra State, Nigeria
Keywords: Artificial Intelligence, Igbo language, lexical ambiguity, machine translation, misiterpretation, AI translation errors

Abstract

Lexical ambiguity and incorrect word substitutions pose considerable challenges in integrating the Igbo language into AI-driven translation tools and search engines. As a tonal language with complex morphological structures, Igbo often includes words that carry multiple meanings depending on context and tone. Unfortunately, most AI-powered translation and text-processing systems lack the necessary linguistic frameworks to accurately interpret these variations, resulting in frequent misinterpretations and erroneous word substitutions. This study focused on the translation errors encountered by Artificial Intelligence (AI) systems when translating the Igbo language, focusing on lexical ambiguity, misinterpretation, and incorrect word substitutions due to contextual deficiencies. The research examines the limitations of AI in handling Igbo’s complex structure and semantics, which are crucial for accurate translation. Through a comparative analysis of AI-generated translations using tools such as Google Translate, Microsoft Translator, and DeepL, alongside human translations, this study identifies key areas where AI systems struggle, particularly with words that have multiple meanings based on context. The theoretical frameworks of Translation Equivalence Theory and Lexical field Theory are applied to analyze the linguistic challenges involved. Case studies highlighting errors such as lexical ambiguity and misinterpretations provide a detailed look at how AI fails to capture the cultural and contextual sensitivities of Igbo. The study also discusses the implications of these errors on communication and the integrity of the Igbo language, offering insights into how AI translation tools can be improved. The findings emphasize the need for ethical and cultural considerations in AI translation and make recommendations for future research to enhance AI-based translations of African languages, specifically Igbo.

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Published
2025-04-29
How to Cite
Okafor, A. Y. (2025). Examining AI Translation Errors in Igbo: Lexical Ambiguity, Misinterpretation, and Incorrect Word Substitutions Due to Contextual Deficiencies. Indonesian Journal of Learning Studies, 5(1), 46-55. https://doi.org/10.53769/ijls.v5i1.1629
Section
Articles