MT embedded E-learning in India - Challenges for NLP/AI

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Abstract

Indian languages are spoken by more than 90% of its population while most of the higher education happens in English medium. The policy makers in Indian government have realized that by introducing multilingual education electronically, they can reach out to the remotest corner of India and educate all in their mother tongue. The New Education Policy (NEP) draft just released by the government puts a heavy focus on mother tongues in education. The recent initiatives and focus on Natural Language Processing/ Artificial Intelligence (NLP/AI) in education through e-learning is not too surprising in this context. The paper presents the current initiatives in these directions by the government of India, surveys available NLP technologies particularly those for automatic translation of educational content developed by academia and industry and focuses on the Maithili language community. India's education needs are diverse and the success of e-learning depends heavily on the availability of necessary NLP tools in all languages. Almost all of major scheduled Indian languages are considered "resource-poor". While some of these languages may have the basic tools, they lack quality translation tools for delivering education in native language. The situation is more challenging in those languages where even the most basic resources and tools do not exist. Maithili-a language of Bihar and Nepal is such a language. The paper also presents an effort to develop MT resources and tools for Maithili and its application in delivering multilingual content for education.

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Nidhi, R., Singh, T., & Lobiyal, D. K. (2019). MT embedded E-learning in India - Challenges for NLP/AI. International Journal of Engineering and Advanced Technology, 9(1), 2577–2582. https://doi.org/10.35940/ijeat.A9348.109119

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