Bilingual Lexicon Extraction from Arabic-English Parallel Corpora with a View to Machine Translation

Sabtan, Yasser Muhammad Naguib

doi:10.2139/ssrn.2795900

Cited by 6 publications

(4 citation statements)

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“…Reverso, Word Reference, Glosbe) that can be considered as the most recommended first step for searching the contextual usage of a lexical item before coming to a decision on an equivalent. Parallel corpora are useful tools to enhance the user's knowledge of equivalence between languages ( Alkahtani, 2015;Sabtan, 2016;Alotaibi, 2017). -There is an abundance of available and accessible ODs in the market today.…”

Section: Pedagogical Implicationsmentioning

confidence: 99%

Female Translation Students' Knowledge and Use of Online Dictionaries and Terminology Data Banks: A Case Study

Sabbah

Alsalem

2018

SSRN Journal

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This study aims to determine whether translation students at an undergraduate translation program have sufficient awareness of the availability and usability of online vocabulary and terminology search tools that can be of valid assistance to a translator. The study surveyed 50 female translation students of the Translation Program at Prince Sultan University, Saudi Arabia. The survey consisted of questions about knowledge and use patterns and included texts for translating between English and Arabic. Results show that although the students know and use a variety of online resources, they still lack in awareness of some of the very useful ones, and a small minority of the students does not use monolingual dictionaries at all. Analysis of the students' translations of selected terms reveals that availability of excellent online resources is not enough to prevent mistranslations if the students cannot select the right equivalent. The study has implications for lexicographers about the dictionary features most frequently used by translators-to-be. It also provides pedagogical tips for translator trainers who should guide their students to making use of the full potential of online dictionaries and term banks in order to achieve better translation outcomes.

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Section: Pedagogical Implicationsmentioning

confidence: 99%

Female Translation Students' Knowledge and Use of Online Dictionaries and Terminology Data Banks: A Case Study

Sabbah

Alsalem

2018

SSRN Journal

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“…The lexico-semantic problems persist in the translated outputs despite the existence of word sense disambiguation (WSD) techniques .This might be logical due to the special case of the Arabic morphological system as characterized with being highly inflectional [47] and the unique orthographic system of Arabic with its loose and nonconventionalized scheme of writing [48]. The morphological and orthographic systems of the Arabic vernacular languages seem to be even more complicated and pose more challenge.…”

Section: The Reason Of This Inherent Poor Quality Of Googlementioning

confidence: 99%

An Evaluation of the Accuracy of the Machine Translation Systems of Social Media Language

Sabtan¹,

Hussein²,

Ethelb³

et al. 2021

IJACSA

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In this age of information technology, it has become possible for people all over the world to communicate in different languages through social media platforms with the help of machine translation (MT) systems. As far as the Arabic-English language pair is concerned, most studies have been conducted on evaluating the MT output for the standard varieties of Arabic, with fewer studies focusing on the vernacular or colloquial varieties. This study attempts to address this gap through presenting an evaluation of the performance of MT output for vernacular or colloquial Arabic in the social media domain. As it is currently the most widely used MT system, Google Translate (GT) has been chosen for evaluating the reliability of its output in the context of translating the Arabic colloquial language (i.e., Egyptian/Cairene Arabic variety) used in social media into English. With this goal in mind, a corpus consisting of Egyptian dialectal Arabic sentences were collected from social media networks, i.e., Facebook and Twitter, and then fed into GT system. The GT output was then evaluated by three human translators to assess their accuracy of translation in terms of adequacy and fluency. The results of the study show that several translation problems have been spotted for GT output. These problems are mainly concerned with wrong equivalents, inappropriate additions and deletions, and transliteration for out-of-vocabulary (OOV) words, which are mostly due to the literal translation of the Arabic vernacular sentences into English. This can be due to the fact that Arabic vernacular varieties are different from the standard language for which MT systems have been basically developed. This, consequently, necessitates the need to upgrade such MT systems to deal with the vernacular varieties.

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“…The researcher shows that the MT output of Google Translate includes lexical and syntactic errors which affect the quality of translation. In fact, as pointed out by Sabtan (2016Sabtan ( , 2019, Arabic is challenging for MT as it is known for being a free word order language with a morphologically complex system. In another recent study Alsalem (2019) indicates that post-editing of Google Translate output is beneficial to student translators' development of their translation skills.…”

Section: Literature Reviewmentioning

confidence: 99%

Teaching Arabic Machine Translation to EFL Student Translators: A Case Study of Omani Translation Undergraduates

Sabtan¹

2020

IJEL

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The present paper describes a machine translation (MT) course taught to undergraduate students in the Department of English Language and Literature at Dhofar University in Oman. The course is one of the major requirements for BA in Translation. Fifteen EFL translation students who were in their third year of study were enrolled in the course. The author presents both the theoretical and practical parts of the course. In the theoretical part, the topics covered in the course are outlined. As for the practical part, it focuses on the translation students’ post-editing of online MT output. This is beneficial to the students as free online MT systems can potentially be used as a means for improving student translators’ training and EFL learning. This is achieved through subjecting MT output to analysis or post-editing by the students so that they can focus on the differences between the source and target languages. With this goal in mind, assignments were given to the students to post-edit the Arabic and English MT output of three free online MT systems (Systran, Babylon and Google Translate), discuss the linguistic problems that they spot for each system and choose the one that has the fewest number of errors. The results show that the students, with varying degrees of success, have managed to identify some linguistic errors with the MT output for each MT system and thus produced a better human translation. The paper concludes that there is a need to incorporate MT courses in translation departments in the Arab world, as integrating technology into translation curricula will have great effect on student translators’ training for their future career as professional translators.

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Bilingual Lexicon Extraction from Arabic-English Parallel Corpora with a View to Machine Translation

Cited by 6 publications

References 10 publications

Female Translation Students' Knowledge and Use of Online Dictionaries and Terminology Data Banks: A Case Study

Female Translation Students' Knowledge and Use of Online Dictionaries and Terminology Data Banks: A Case Study

An Evaluation of the Accuracy of the Machine Translation Systems of Social Media Language

Teaching Arabic Machine Translation to EFL Student Translators: A Case Study of Omani Translation Undergraduates

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