Open AccessTHE ACCURACY OF GOOGLE TRANSLATION SYSTEM IN TRANSLATING REFERENTIAL PRONOUN (THAT) WITHIN THE LITERARY TEXTS
Author(s) -
Omar Ali Hussein Al-Ani,
Ahmed Adel Nouri Al-Ani
Publication year - 2021
Publication title -
international journal of humanities and educational research
Language(s) - English
Resource type - Journals
ISSN - 2757-5403
DOI - 10.47832/2757-5403.5-3.17
Subject(s) - computer science , documentation , machine translation , pronoun , consistency (knowledge bases) , natural language processing , linguistics , newspaper , artificial intelligence , machine translation software usability , example based machine translation , translation (biology) , class (philosophy) , information retrieval , sociology , philosophy , biochemistry , chemistry , messenger rna , media studies , gene , programming language
The demand for language translation has greatly increased in recent times due to increasing international communication and the need for information exchange. Most material needs to be translated, including scientific and technical documentation, instruction manuals, legal documents, textbooks, publicity leaflets, newspaper reports etc. Some of this work is challenging and difficult but mostly it is boring and repetitive and requires consistency and accuracy. It is becoming difficult for professional translators to meet the increasing demands of translation. In such a situation the machine translation can be used as a substitute. This study offers a brief but condensed overview of Machine Translation (MT). It aims at identifying the percentages of Google translation system in translating referential pronoun (that) within the literary text. The sample of the study consists of three literary texts. The study used percentages to detect the accuracy of Google translation system. The results showed that percentage of accuracy Google translation is 100% in translating referential pronoun (that) within the literary texts. It’s recommended that Google translation system might be used formally by English teachers and translators in order to get benefit from the time and the cost inside class and translators centers and educational subjects. Keywords: Google, Machine Translation, Human Translation