The Linguistic Problem-based Effect of Using Machine Translation in Mobile & Computer Apps : English and Arabic as a case study

Abstract

Because of the growing utility of technology-based learning especially translation and the rapid expansion of internet all over the world, it becomes an urgent need to research for the pros and cons of machine learning for its widely used. This paper aims at investigating the Arabic-English morphological, syntactic and semantic errors made by the machine applications with special reference to Google Translate app, and it also aims at the role of machine in learning. The paper discusses linguistics effects of machine translation in language learning. The paper also discusses the main linguistic problems and difficulties of machine translation conducted by mobile and computer applications for English and Arabic in addition to recommending certain steps and solutions which help in overcoming such difficulties. The paper deeply attempts to find recommendations for getting good quality of Arabic machine translation and to take them into account by developers of the learning apps in smartphones and computers.

The paper attempts to answer the following questions. What are the effects of errors made by the translation of Google Translate in Arabic upon users of electronic apps? What are the causes of these errors and how do these errors affect the translation quality? How to correct these errors and overcome them? The paper has adopted the analysis by analyzing certain sentences as samples translated by Google Translate app, smartphones dictionaries and Toolkit app and other internet websites specialized in machine translation.