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Paper title
Using Neural Translation Machine (NTM) Algorithm To Bridge Language Barrier for Igbo Students in China.

Paper author
Otuu Obinna and Edim Bassey Edim

Author Email
[email protected]

Abstract
Understanding a course which is taught in a language, not known to students is the major hitch in international education. This poses a measure challenge that generates concerns among foreign students who are mostly subjected to learning the foreign language of the institutional host country, thereby adding a year or more to the programme depending on when the student successfully scrambles over the language huddles. This paper reviewed related literature and presented a Neural Machine Translation algorithm which converts a speech made in Chinese language, through an audio input device, into Igbo Language. The study recommends that this technology be harnessed and implemented as to make learning seamless, especially for visually impaired Igbo students in China. Keywords: Audio, Text, Translator, Classroom, language.


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