رهانات المترجم البسري بين ضفتي الترجمة الألية العصبية و الترجمة اللآلية الاحصائية - دراسة مقارنة -

Abstract

Automated translation is the process of translating text using software that is trained in language analysis and translation into another language. This process involves identifying structural components of words such as Arabic-related pronouns. This study aims to identify the two most important systems of machine translation: statistical machine translation and neural machine translation while illustrating the difference between them. The neural machine translation system works in a distinctive way by accurately and reliably simulating the way the human brain performs certain tasks, allowing for increased translation performance. The statistical translation system relies mainly on the data stored in the translation programme, and when the user inserts a specific sentence, the program makes approaches to identical or similar sentences and presents the result with the highest frequency, hence its statistical name. We have taken Reverso's website in statistical machine translation and Google Translate's nerve machine translation website as models in our translation and their effectiveness in translating into Arabic. Despite the accepted results provided by these sites, any mistranslation in these sites may lead to misinterpretations and thus various translation errors that relate to both meaning and form such as literal translation, spelling errors, semantic grammatical errors, etc. Thus, it became necessary for researchers to develop a hybrid model by integrating the translation memory-based machine translation system of the statistical system with the synthetic networks of the neuromotor translation system to overcome the problem of erroneous recruitment of the term.