Exploring the Performance of Tagging for the Classical and the Modern Standard Arabic by Dia AbuZeina, Taqieddin Mostafa Abdalbaset

“…In this paper, we examine the performance of a modern standard Arabic (MSA) based tagger for the classical (i.e., traditional or historical) Arabic. …”
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WORD FORMATION AS A MODERNIZATION TOOL OF MODERN STANDARD ARABIC (FROM THE POINT OF VIEW OF ARABIC AND WESTERN LINGUISTS) by Y. S. Ayvazyan

“…The current article is devoted to the analysis of word formation processes in Modern Standard Arabic from the point of view of Arabic and Eastern linguists. …”
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Live Interpreting during the Covid-19 Pandemic: The Medium, the Mode and the Model by Muhammad Gamal

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An XML Approach of Coding a Morphological Database for Arabic Language by Mourad Gridach, Noureddine Chenfour

“…We present an XML approach for the production of an Arabic morphological database for Arabic language that will be used in morphological analysis for modern standard Arabic (MSA). Optimizing the production, maintenance, and extension of morphological database is one of the crucial aspects impacting natural language processing (NLP). …”
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The Key English Pronunciation Difficulties for Egyptian EFL Learners by Hasnaa Hasan Sultan Abdelreheem

“…The project involves both contrastive analysis (of the phonological systems of English, Egyptian Arabic and Modern Standard Arabic) as well as error analysis. While the significance of contrastive analysis lies in helping EFL teachers predict the problematic aspects (Al-Saqqaf and Vaddapalli 2012, 56), error analysis would provide them with the actual problems encountered by the learners and the extent of their seriousness.…”
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Patterns of Consonant Clusters in Word Initial, Medial, and Final Positions in Yemeni Arabic by Muhammed Jubran AL-Mamri

“…There are features of consonant clusters in Yemeni Arabic which differ from Modern Standard Arabic and some other Arabic dialects. In Yemeni Arabic, there are 29 consonants and 10 vowels, 5 long and 5 short vowels. …”
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Enhancing Arabic text-to-speech synthesis for emotional expression in visually impaired individuals using the artificial hummingbird and hybrid deep learning model by Mahmoud M. Selim, Mohammed S. Assiri

“…The AMCDD-AHODL approach is examined using the Modern Standard Arabic dataset containing 1229 records. The performance validation of the AMCDD-AHODL approach portrayed a superior accuracy value of 95.80 % compared to the existing ML and DL models. …”
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