A Comparative Study of English-Persian Translation of Neural Google Translation

Document Type : Research Paper

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Shahid Bahonar University of Kerman

Abstract

Many studies abroad have focused on neural machine translation and almost all concluded that this method was much closer to humanistic translation than machine translation. Therefore, this paper aimed at investigating whether neural machine translation was more acceptable in English-Persian translation in comparison with machine translation. Hence, two types of text were chosen to be translated by Google Translate. The inputs have been translated in two distinctive methods. The outputs were investigated by the descriptive-comparative human analysis model of Keshavarz. Consequently, the results revealed that approximately the same errors were found in both methods. However, semantic aspects were improved.

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