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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