Analysing English-Arabic Machine Translation

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A01=Zakaryia Almahasees
Author_Zakaryia Almahasees
Bilingual Corpora
Cat Tool
Category=CJ
Collocation Errors
computational linguistics
Computer Aided Translation
corpus-based analysis
English Arabic Translation
English Collocations
eq_bestseller
eq_dictionaries-language-reference
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
eq_non-fiction
error analysis linguistics
Fluency Results
Fluent Translation
Google Translate
Grammatical Collocations
Libyan Political Agreement
machine translation system comparison
Microsoft Translator
MT
MT Output
MT Research
MT System
MTE
natural language processing
NMT
Omission Errors
RBMT
Reference Translation
SDL Trados
SDL Trados Studio
ST Meaning
translation adequacy fluency
translation evaluation methods
Word Order Errors

Product details

  • ISBN 9781032042275
  • Weight: 160g
  • Dimensions: 156 x 234mm
  • Publication Date: 31 May 2023
  • Publisher: Taylor & Francis Ltd
  • Publication City/Country: GB
  • Product Form: Paperback
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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.

Dr. Zakaryia is an Assistant Professor of Translation at the Department of English Language and Translation at Applied Science Private University, Jordan. He obtained his PhD in Translation Studies, from The University of Western Australia, Australia (2020). Zakaryia also holds a Master's and Bachelor’s in English Language and Literature. His research interests include Translation Theories, Translation Evaluation, Comparative Translation, and Machine Translation (MT), corpus linguistics, and Computer Aided Translation (CAT).

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