Language Errors in Machine Translation of Scientific Biological Texts from English to Arabic: The Case of Google Translate
Date
2019-05-16
Authors
Alawneh, Hanan
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Journal ISSN
Volume Title
Publisher
Hanan Jamal Alawneh
Abstract
Machine translation has planted its roots deeply in research domains since it becomes the first aid for survival in this era of "globalization". Thus, the present research explores the areas of efficiency/deficiency in Google Translate performance in scientific biological texts translation from English to Arabic. More specifically, the research aims to test GT performance at two levels: sentence and paragraph levels. Thus, Catford’s translation shifts (1965), Halliday and Hassan's model of cohesive devices (1976) and types of paragraphs frequently used in scientific texts are the main tools used to judge GT output. Finally, the researcher attempts to propose solutions for the errors encountered to enhance GT performance in this particular text type to help GT produce translations with high accuracy rates.
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Keywords
Language Errors in Machine Translation of Scientific Biological Texts from English to Arabic: The Case of Google Translate