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...

In this paper, we present the details of creating a pilot Arabic proposition bank (Propbank). Propbanks exist for both English and Chinese. However the morphological and syntactic expression of linguistic phenomena in Arabic yield a very different type of process in creating an Arabic propbank. Hence, we highlight those characteristics of Arabic that make creating a propbank for the language a ...

The Quranic Arabic Corpus (http://corpus.quran.com) is an annotated linguistic resource with multiple layers of annotation including morphological segmentation, part-of-speech tagging, and syntactic analysis using dependency grammar. The motivation behind this work is to produce a resource that enables further analysis of the Quran, the 1,400 year old central religious text of Islam. This paper...

arabic languages is not a foreign language for us as iranins is the language of our religion and islamic culture. thus to protect our religion and culture. we should learn it. because arabic is not our native language. so one way to learn it is through the comparison and contrast of structure and grammatical points of arabic and persian. this issue is very helpful in translating a text. this ar...

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...

We demonstrate a data collection and analysis system that can be used to analyze the relative contributions of dialect dependent variation in the lexical of speech-like Arabic text. We utilize Latent Dirichlet Allocation (LDA), a generative Probabilistic modeling method, to analyze a phonetic Latin Spelled Arabic online chat corpus. The corpus produces different word choices and word relations ...

Text classification is the process of assigning a text or a document to various predefined classes or categories to reflect their contents. With the rapid growth of Arabic text on the Web, studies that address the problems of classification and segmentation of the Arabic language are limited compared to other languages, most of which implement word-based and feature extraction algorithms. This ...

Segmentation of clitics has been shown to improve accuracy on a variety of Arabic NLP tasks. However, state-of-the-art Arabic word segmenters are either limited to formal Modern Standard Arabic, performing poorly on Arabic text featuring dialectal vocabulary and grammar, or rely on linguistic knowledge that is hand-tuned for each dialect. We extend an existing MSA segmenter with a simple domain...

In the Arabic-English and English-Arabic translation activities, the interface is very significant. For translation in the Arabic language, many issues need to be addressed. The existing systems have some problems and research has been initiated to improve. Transliteration is an important component of the translation. We in this study propose a system of interface for Arabic transliteration. Th...

This paper reports on the application of the Text Attribution Tool (TAT) to profiling the authors of Arabic emails. The TAT system has been developed for the purpose of language-independent author profiling and has now been trained on two email corpora, English and Arabic. We describe the overall TAT system and the Machine Learning experiments resulting in classifiers for the different author t...