Alasmari, J, Watson, JCE and Atwell, E orcid.org/0000-0001-9395-3764 (2018) A Contrastive Study of the Arabic and English Verb Tense and Aspect A Corpus-Based Approach. PEOPLE: International Journal of Social Sciences, 3 (3). pp. 1604-1615. ISSN 2454-5899
Abstract
There is so far only limited research that applies a corpus-based approach to the study of the Arabic language. The primary purpose of this paper is therefore to explore the verb systems of Arabic and English using the Quranic Arabic Corpus, focussing on their similarities and differences in tense and aspect as expressed by verb structures and their morphology. Understanding the use of different verb structures, participles, and auxiliary verbs that are used to indicate time and actions may be one way to improve translation quality between Arabic and English. In order to analyse these forms, a sub-corpus of two Arabic verb forms and their translations in English were created. The Arabic verbs and their English translations were then compared and analysed in terms of syntactic and morphological features. The following English translations of the Quran were used: Sahih International, Pickthall, Yusuf Ali, Shakir, Muhammad Sarwar, Mohsin Khan, Arberry. The analysis shows a considerable disagreement between the Arabic verb tense and aspect, and their translations. This suggests that translating Arabic verbs into English is fraught with difficulty. The analysis of the corpus data can be categorised and calculated and can then potentially be used to improve the translation between the two languages.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | This work is licensed under the Creative Commons Attribution-Non-commercial 4.0 International License. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc/4.0/ or send a letter to Creative Commons, PO Box 1866, Mountain View, CA 94042, USA. |
Keywords: | Arabic Verb, Verb Corpus, Translation |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Computing (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 23 May 2018 11:08 |
Last Modified: | 08 Jul 2019 15:09 |
Status: | Published |
Publisher: | GRDS Publishing |
Identification Number: | 10.20319/pijss.2018.33.16041615 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:131135 |