This paper presents DIWAN, an annotation interface for Arabic dialectal texts. While the Arabic dialects differ in many respects from each other and from Modern Standard Arabic, they also have much in common. To facilitate annotation and to make it as efficient as possible, it is therefore not advisable to treat each Arabic dialect as a separate language, unrelated to the other variants of Arab...

We present a method for generating Colloquial Egyptian Arabic (CEA) from morphologically disambiguated Modern Standard Arabic (MSA). When used in POS tagging, this process improves the accuracy from 73.24% to 86.84% on unseen CEA text, and reduces the percentage of out-ofvocabulary words from 28.98% to 16.66%. The process holds promise for any NLP task targeting the dialectal varieties of Arabi...

Stemming is an essential processing step in a wide range of high level text processing applications such as information extraction, machine translation and sentiment analysis. It is used to reduce words to their stems. Many stemming algorithms have been developed for Modern Standard Arabic (MSA). Although Arabic tweets and MSA are closely related and share many characteristics, there are substa...

Statistical machine translation for dialectal Arabic is characterized by a lack of data since data acquisition involves the transcription and translation of spoken language. In this study we develop techniques for extracting parallel data for one particular dialect of Arabic (Iraqi Arabic) from out-ofdomain corpora in different dialects of Arabic or in Modern Standard Arabic. We compare two dif...

Tunisian Arabic is a dialect of the Arabic language spoken in Tunisia. Tunisian Arabic is an under-resourced language. It has neither a standard orthography nor large collections of written text and dictionaries. Actually, there is no strict separation between Modern Standard Arabic, the official language of the government, media and education, and Tunisian Arabic; the two exist on a continuum ...

In this paper, a novel for Query Translation and Expansion for enabling English/Arabic CLIR for both normal and OCR-Degraded Arabic Text model has been proposed, implemented, and tested. First, an English/Arabic Word Collocations Dictionary has been established plus reproducing three English/Arabic Single Words Dictionaries. Second, a modern Arabic Corpus has been built. Third, a model for simu...

OF THESIS THE ARABIC PARTICLES ‘INNA WA AḪAWA ̄TU-HA ̄ ’ AT THE SYNTAX-SEMANTICS INTERFACE In Arabic inna wa-aḫawātu-hā ‘inna and its related sisters’ are traditionally considered as verb-like particles. They are specified as introducing equational sentences and change their constituents’ case to a different pattern from what verbs do. Therefore, they are called nawāsiḫ in Arabic, or words that c...

Arabic morphology poses special challenges to computational natural language processing systems. Its rich morphology and the highly complex word formation process of roots and patterns make computational approaches to Arabic very challenging. In this paper we present an approach for morphological analysis and generation of Modern Standard Arabic (MSA). Our approach is based on Arabic morphologi...

The article deals with special aspects of Arabic Teaching in Tatar schools and madrasas at the end of XIX – beginning of XX centuries in the light of Arabic textbooks preserved up modern times. The author investigates continuity of Arabic Linguistic traditions in writing and publishing books on Arabic Grammar for Tatars. Tatar teachers of Arabic tried to find their own approach to an educationa...

This paper presents a comprehensive NLP system by Melingo that has been recently developed for Arabic, based on Morfix – an operational formerly developed highly successful comprehensive Hebrew NLP system. The system discussed includes modules for morphological analysis, context sensitive lemmatization, vocalization, text-to-phoneme conversion, and syntactic-analysis-based prosody (intonation) ...