Machine translation of classical Arabic into English using rule-based approach

Huda Alhusain Ali Hebresha (P52689)

Please use this identifier to cite or link to this item: https://ptsldigital.ukm.my/jspui/handle/123456789/476566

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DC Field	Value	Language
dc.contributor.advisor	Mohd. Juzaiddin Ab Aziz, Dr.	-
dc.contributor.author	Huda Alhusain Ali Hebresha (P52689)	-
dc.date.accessioned	2023-10-06T09:21:13Z	-
dc.date.available	2023-10-06T09:21:13Z	-
dc.date.issued	2012-10-04	-
dc.identifier.other	ukmvital:120386	-
dc.identifier.uri	https://ptsldigital.ukm.my/jspui/handle/123456789/476566	-
dc.description	Recently, Arabic machine translation has been taking place in machine translation projects and so, many researches have been carried out to improve and enhance the quality of translation from and into Arabic. This research concentrates on the translation of Classical Arabic (CA) rather than Modern Standard Arabic. The problems of this research are the difficulty of delivering the appropriate meaning of the Classical Arabic term in the target language (English), different sentence structure between two languages, and word agreement and ordering problem. The main aim of our work is to create an Arabic-English machine translation system to translate text from Classical Arabic (CA) into English using rule-based approach. To achieve this objective; first, we modified a lexical database to contain vocabulary which related to the environment of Classical Arabic. Then we build and implemented a machine translation prototype called (CAMT) to overcome the difficulties of translation of Classical Arabic to English. Our system includes three phases which are analysis, transfer and generation phase. Firstly, in the analysis phase the CA input text is analysed morphologically and syntactically. Morphological analysis produces information about the part-of-speech of each word in the CA input text and its sub-category such as (Number, gender, tense, etc.). The work of the syntactical analysis is to check the correctness of sentence grammatically and in spelling. Secondly, in transfer stage we use the information from previous phase to acquire reasonable rule of the CA input text structure and its equivalent rule in the target language (English). The translation of each word must be chosen from the dictionary in this step. In the final phase, using the information from the transfer stage the Arabic source text will be generated to obtain the target text in English. The evaluation process of this work is done by comparing the output produced by our system with the original human translation. We have carried out two experiments to evaluate CAMT system which are: automatic evaluation using iBLEU metric and human judgment evaluation. The 1-gram results produced by iBLEU algorithm show that the accuracy of CAMT is nearly 89.4%, while human judgment evaluation results gave CAMT system around 91.0% accuracy. The results produced by both experiments prove that the system provides good results.,Certification of Master's / Doctoral Thesis" is not available	-
dc.language.iso	eng	-
dc.publisher	UKM, Bangi	-
dc.relation	Faculty of Information Science and Technology / Fakulti Teknologi dan Sains Maklumat	-
dc.rights	UKM	-
dc.subject	Arabic language -- Machine translating	-
dc.subject	Computational linguistics	-
dc.subject	Machine translating	-
dc.subject	Information storage and retrieval systems	-
dc.subject	Universiti Kebangsaan Malaysia -- Dissertations	-
dc.subject	Dissertations, Academic -- Malaysia	-
dc.title	Machine translation of classical Arabic into English using rule-based approach	-
dc.type	theses	-
dc.format.pages	132	-
dc.identifier.callno	Z699.H384 2012 3 tesis	-
dc.identifier.barcode	005340(2021)(PL2)	-
Appears in Collections:	Faculty of Information Science and Technology / Fakulti Teknologi dan Sains Maklumat

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