Abstract
The computer era has led to new opportunities in communication and knowledge sharing that were never had before, and it has also endangered the diversity of languages in the world and increased the disparity in technology. As more languages in the world are at risk of extinction (estimated to be 40 percent), and many communities do not meaningfully access digital tools in their native languages, the importance of machine learning in language preservation is greater. This study discussed the application of machine learning technologies to document, support, and revive endangered languages and ensure digital inclusion. Automatic speech recognition had a major effect of reducing the time spent in transcription of endangered languages to almost an instant output with just a few training samples. Machine translation systems, such as new multilingual projects, have increased their languages to cover more than 200 languages and enhanced the quality of translations done on languages that were previously ignored. In addition to documentation, digital platforms, educational technologies, and available language resources that helped minority language communities were also developed because of machine learning. Overall, this paper demonstrated that machine learning offers useful means to solve linguistic vulnerability and cut digital inequality in the ever-connected world.
Keywords
Machine Learning, Language Preservation, Digital Inclusion, Endangered Languages, Natural Language Processing, Language Diversity, Old Data Sovereignty, Limited Resource Languages, And Digital Equity.
Citations
IRE Journals:
Nneoma Udeze "The Role of Machine Learning in Preserving Languages and Promoting Digital Inclusion" Iconic Research And Engineering Journals Volume 9 Issue 6 2025 Page 2335-2340 https://doi.org/10.64388/IREV9I6-1713136
IEEE:
Nneoma Udeze
"The Role of Machine Learning in Preserving Languages and Promoting Digital Inclusion" Iconic Research And Engineering Journals, 9(6) https://doi.org/10.64388/IREV9I6-1713136
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