Analysing English-Arabic Machine Translation: Google Translate, Microsoft Translator and Sakhr

di Zakaryia Almahasees (Autore)

Taylor & Francis Ltd, 2023

Machine Translation (MT) has become widely used throughout the world as a medium of communication between those who live in different countries and speak different languages. However, translation between distant languages constitutes a challenge for machines. Therefore, translation evaluation is poised to play a significant role in the process of designing and developing effective MT systems. This book evaluates three prominent MT systems, including Google Translate, Microsoft Translator, and Sakhr, each of which provides translation between English and Arabic. In the book Almahasees scrutinizes the capacity of the three systems in dealing with translation between English and Arabic in a large corpus taken from various domains, including the United Nation (UN), the World Health Organization (WHO), the Arab League, Petra News Agency reports, and two literary texts: The Old Man and the Sea and The Prophet. The evaluation covers holistic analysis to assess the output of the three systems in terms of Translation Automation User Society (TAUS) adequacy and fluency scales. The text also looks at error analysis to evaluate the systems’ output in terms of orthography, lexis, grammar, and semantics at the entire-text level and in terms of lexis, grammar, and semantics at the collocation level. The research findings contained within this volume provide important feedback about the capabilities of the three MT systems with respect to English<>Arabic translation and paves the way for further research on such an important topic. This book will be of interest to scholars and students of translation studies and translation technology.

• Autore: Zakaryia Almahasees
• Editore: Taylor & Francis Ltd
• Collana: Routledge Studies in Translation Technology
• Anno: 2023
• Rilegatura: Paperback / softback
• Pagine: 202 p.
• Dimensioni: 234 x 156 mm
• Peso: 331 gr.
• EAN: 9781032042275

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