Machine Translation Quality of Khalil Gibran’s The Prophet

Abstract

Machine translation (MT) systems are widely used throughout the world freely or at low cost. The spread of MT entails a thorough analysis of translation produced by such translation systems. The present study evaluates the capacity of two MT systems-Google Translate and Microsoft Bing translator-in translation from Arabic into English of Khalil Gibran's literary masterpiece -The Prophet (2000). The question that arises in the study is could we trust MT in the translation of literary masterpieces across languages and particularly from Arabic to English? How close does MT output to human translation? To conduct that, the study is adopted Bilingual Evaluation Understudy (BLEU) of Papineni (2000). MT output analysis showed that MT is not accurate, intelligible and natural in translating literary texts due to the difficulty of literary texts, as they are full of metaphors and cultural specifications. Besides, there are some linguistic errors: lexical, syntactic and misinformation. The study also found that both systems provided similar translation for the same input due to either the use of similar MT approach or learning from previous translated texts. Moreover, both systems in some instances, achieve good results at the word level, but bad results at collocation units. The study also showed that automatic translation is insufficient for providing a full analysis of MT output because all automatic metrics are misleading due to dependence on text similarity to a reference human translation. For future research, the study recommended conducting a correlative study that combines manual and automatic evaluation methods to ensure best analysis of MT output. Machine Translation (MT) is still far from reaching fully automatic translation of a quality obtained by human translators. www.awej-tls.org 152 Introduction Machine Translation (MT) is the subfield of computational linguistics that concern in the using of computer software in translation across human languages. Machine Translation is an interrelated field that covers three main interrelated knowledge disciplines: translation, linguistics and translations' software. In this regard, Almahasees (2017, p.1) presents a comprehensive definition of MT as " the use of computers in the process of translation from one natural language into another. " He adds that the integration of Translation and technology has resulted in " automatic translation or translation by a computer called Machine Translation. " He (2017, p.1) accentuates that such integration " allow computers to translate from one language into another. " Today, most of the scientific contribution is written in English, and thus globalization has brought English as an international language, which becomes the language of instruction in most global universities. In the case of people who do not master English, they tend to use MT as translation aid in their studies. Actually, MT is used widely, and there is a set of translation software that allowed the potential users to translate full documents, more quickly and freely or at low cost than human translators can. The most important aim of MT is to generate a translation that is similar to human translation, which is acceptable by human translators, clients, and readers. Trotsky (2016), product lead of Google Translate, shows that Google translate users extend more than 500 million per day. He mentions that most translation is conducted " Between English and Spanish, Arabic, Russian,