Seybold Report ISSN: 1533-9211

Abstract

SEMANTIC AND SYNTACTIC AMBIGUITY WHEN TRANSLATING INFLECTIONAL AFFIXES IN INFORMATIVE TEXTS USING MACHINE TRANSLATION (MT) AS A LEARNING TOOL: COMPARATIVE STUDY BETWEEN THREE MT SOFTWARE.


Souda Mohammad M Abdaly, Razan Anwar Ali Hakami


Vol 18, No 5 ( 2023 )   |  Licensing: CC 4.0   |   Pg no: 156-201   |   Published on: 25-05-2023



Abstract
The availability of the internet in our devices makes accessing software easier which causes the increasing involvement of machine translation during the learning process of any kind. As a result, students utilize MT to learn any form of knowledge to make the content understandable to them. However, for language learners, translation is not only a mean to comprehend any form of knowledge, but also as a tool that facilitates the acquisition of a new language. This since they are exposed to the linguistic aspects in depth for both their native language and the new language they are learning. However, MT does not always give precise outcomes especially when dealing with two distant languages like Arabic and English which vary both semantically and syntactically. The current paper aims to investigate whether the inflectional affixes in 20 Arabic informative texts, will create challenges to three MT softwares which are Microsoft Translator, Babylon, and Google translate. This in order to find any semantic and syntactic ambiguity that could hinder the process of learning English. It will also evaluate the MTs outcomes to find out which MTs works the best when translating inflectional affixes and which one is the least effective. This will highlight the role of teachers as mentors to their students while using MT as a learning tool in order to avoid any obstacles raised during that. Additionally, it could increase the awareness of MT developers to address these gaps in the way MT softwares process smaller units like inflectional affixes.


Keywords:
Semantic ambiguity, syntactic ambiguity, inflectional affixes, Machine translation



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