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Advancement in information technology has resulted in massive textual material that is open to appropriation. Due to researchers' misconduct, a plethora of plagiarism detection (PD) systems have been developed. However, most PD systems on the market do not support the Arabic language. In this paper, we discuss the design and construction of an Arabic PD reference corpus that is dedicated to academic language. It consists of (2312) dissertations that were defended by postgraduate students at the University of Jordan (JU) between the years 2001-2016. This Academic Jordan University Plagiarism Detection corpus; henceforth, JUPlag, follows the Dewey decimal classification (DDC) in the way it is structured. The goal of the corpus is twofold: Firstly, it is a database for the detection of plagiarism in student assignments, reports, and dissertations. Secondly, the n-gram structure of the corpus provides a knowledgebase for linguistic analysis, language teaching, and the learning of plagiarism-free writing. The PD system is guided by JU Library's metadata for retrieval and discovery of plagiarism. To test JUPlag, we injected an unseen dissertation with multiple instances of plagiarism-simulated paragraphs and sentences. Experimentation with the system using different verbatim n-gram segments is indeed promising. Preliminary results encourage that permission be sought to enrich this corpus with all the theses in the Thesis Repository of the Union of Arab Universities. The JUPlag corpus is intended to function as an indispensable source for testing and evaluating plagiarism detection techniques. Since the University of Jordan is seeking to become a center for plagiarism detection for Arabic content and being a non-profit organization, it will charge a nominal fee for the use of JUPlag to finance the maintenance and development of the corpus.

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Several tools are developed to facilitate the quantitative analysis of interpretation style, a matter that has hitherto been discussed only in vague terms. These tools can allow the investigation of questions such as: How does an interpreter divide up a source language input, to what extent does he mirror a source language speaker, and to what degree does he practise reformulation? Furthermore, an adaptive monitoring instrument is devised to facilitate the graphic representation of the linear developments of a source language discourse and its simultaneous interpretation equivalent. Not only does it allow the assessment of convergence and divergence between the two discourses, but this also permits commenting on an interpreter's tempo by characterising the narrow and broad periodicity within his discourse, and on his composure and tribulation by describing his consistency and fluency in the discourse.

This study reports on the construction of a one million word English-Arabic Political Parallel Corpus (EAPPC)

We present a collection of morphologically annotated corpora for seven Arabic dialects: Taizi Yemeni, Sanaani Yemeni, Najdi, Jordanian, Syrian, Iraqi and Moroccan Arabic. The corpora collectively cover over 200,000 words, and are all manually annotated in a common set of standards for orthography, diacritized lemmas, tokenization, morphological units and English glosses. These corpora will be publicly available to serve as benchmarks for training and evaluating systems for Arabic dialect morphological analysis and disambiguation.

To compile a modern dictionary that catalogues the words in currency, and to study linguistic patterns in the contemporary language, it is necessary to have a corpus of authentic texts that reflect current usage of the language. Although there are numerous Arabic corpora, none claims to be representative of the language in terms of the combination of geographical region, genre, subject matter, mode, and medium. This paper describes a 100-million-word corpus that takes the British National Corpus (BNC) as a model. The aim of the corpus is to be balanced, annotated, comprehensive, and representative of contemporary Arabic as written and spoken in Arab countries today. It will be different from most others in not being heavily-dominated by the news or in mixing the classical with the modern. In this paper is an outline of the methodology adopted for the design, construction, and annotation of this corpus. DIWAN (Al-Shargi and Rambow, 2015) was used to annotate a one-million-word snapshot of the corpus. DI-WAN is a dialectal word annotation tool, but we upgraded it by adding a new tag-set that is based on traditional Arabic grammar and by adding the roots and morphological patterns of nouns and verbs. Moreover, the corpus we constructed covers the major spoken varieties of Arabic.

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