This paper presents a multi-dialect, multi-genre, human annotated corpus of dialectal Arabic with data obtained from both online newspaper commentary and Twitter. Most Arabic corpora are small and focus on Modern Standard Arabic (MSA). There has been recent interest, however, in the construction of dialectal Arabic corpora (Zaidan and Callison-Burch, 2011a; Al-Sabbagh and Girju, 2012). This wor...

In this paper, we implement a multilingual Statistical Machine Translation (SMT) system for Arabic-English Translation. Arabic Text can be categorized into standard and dialectal Arabic. These two forms of Arabic differ significantly. Different mono-lingual and multi-lingual hybrid SMT approaches are compared. Mono-lingual systems do always result in better translation accuracy in one Arabic fo...

â  examining the effects of teaching contemporary arabic literature through communicative approach â  â  â  maryam jalaei * â  narges ganji ** â  sardar aslani *** â  â  â  â  â  in order to make use of modern methods of teaching in the field of teaching arabic to non- native arab speakers, this study employed communicative approach for the teaching of contemporary arabic literature. thus, this...

We present our correction annotation guidelines to create a manually corrected nonnative (L2) Arabic corpus. We develop our approach by extending an L1 large-scale Arabic corpus and its manual corrections, to include manually corrected non-native Arabic learner essays. Our overarching goal is to use the annotated corpus to develop components for automatic detection and correction of language er...

This paper presents an ESN-based Arabic phoneme recognition system trained with supervised, forced and combined supervised/forced supervised learning algorithms. Mel-Frequency Cepstrum Coefficients (MFCCs) and Linear Predictive Code (LPC) techniques are used and compared as the input feature extraction technique. The system is evaluated using 6 speakers from the King Abdulaziz Arabic Phonetics ...

Dialectal Arabic (DA) refers to the day-to-day vernaculars spoken in the Arab world. DA lives side-by-side with the official language, Modern Standard Arabic (MSA). DA differs from MSA on all levels of linguistic representation, from phonology and morphology to lexicon and syntax. Unlike MSA, DA has no standard orthography since there are no Arabic dialect academies, nor is there a large edited...

This paper reports results of a workshop on the design of electronic content for users with Specific Learning Difficulties (SpLD), particularly Arabic dyslexics. First we shed some light on the nature of the Arabic language and discuss features that account for the unique needs of Arabic users with reading disorders. Then we present recommendations for accessible web design for Arabic content i...

In this paper we investigate the possibility of creating a PoS tagger for Modern Standard Arabic by integrating open-source tools. In particular a morphological analyser, used in the disambiguation process with a PoS tagger trained on classical Arabic. The investigation shows the scarcity of open-source tools and resources, which complicated the integration process. Among the problems are diffe...

A major challenge for statistical machine translation (SMT) of Arabic-to-English user-generated text is the prevalence of text written in Arabizi, or Romanized Arabic. When facing such texts, a translation system trained on conventional Arabic-English data will suffer from extremely low model coverage. In addition, Arabizi is not regulated by any official standardization and therefore highly am...

Part-of-Speech (POS) tagging is a key step in many NLP algorithms. However, tweets are difficult to POS tag because they are short, are not always written maintaining formal grammar and proper spelling, and abbreviations are often used to overcome their restricted lengths. Arabic tweets also show a further range of linguistic phenomena such as usage of different dialects, romanised Arabic and b...