Translating Literary Texts: Human Vs. Machine Translation

Abstract

This study aimed to investigate the proficiency of Google Translate in translating literary texts from English into Arabic. Therefore, 12 literary texts were selected from well-known English novels translated by human translators into Arabic. Then these selected texts were given to Google Translate to translate them into Arabic, and its outputs were analyzed and compared to the human translations. Depending on the comparative analysis of human translation and Google translation, we found that human translation was more effective, natural and readable than Google translation. In other words, human translators were more professional than Google in translating literary texts. For more clarification, Google’s dominating strategy in rendering these literary texts into Arabic was literal translation. Moreover, Google neither made use of deletion strategy nor frequently resorted to insertion strategy to help in producing natural and readable translations. On the other hand, insertion and deletion strategies were widely used by human translators to avoid ambiguity. Also, human translators sometimes resorted to the strategy of compensation of meaning loss to make their translations clearer and more understandable. It was also found that both human translators and Google utilized the transliteration strategy in rendering ST proper nouns into the TL, but human translators always accompanied it with the addition strategy. Human translators depended on context more than Google, so their translation was more accurate and effective. Furthermore, Google followed ST style whereas human translators followed TL style, so human translations are natural and acceptable. Human translators also outdid Google in making accurate and literary lexical choices.