We are facing an informational flood of various languages as a result of the advent of information and communication technology and the democratisation of Internet content creation. Newspapers and news portals both contribute significantly to this material, making it difficult to understand the sheer volume of daily circulating data on the web or in print. Manually managing and translating is admittedly difficult, and even traditional IT tools fail to produce results in all languages. To address this problem, we propose experimenting with deep learning for multilingual machine translation. This paper describes and evaluates our newly developed neural text-to-text translation method. The corpora elaboration and two deep neural processing modules for machine translation were used to create this framework. The device provides users with an ergonomic interface that displays the corresponding translated sentences to the sentences they fed it.
Author (s) Details
Laboratory LRIT, Faculty of Science Rabat, University Mohammed V, Rabat, Morocco.
Dr. Fadoua Ataa Allah
Computer Science Studies, Information Systems and Communication Center, Royal Institute of the Amazigh Culture, Rabat, Morocco.
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