Natural language processing technology for the dialects of Arabic is still in its infancy, due to the problem of obtaining large amounts of text data for spoken Arabic. In this paper we describe the development of a part-of-speech (POS) tagger for Egyptian Colloquial Arabic. We adopt a minimally supervised approach that only requires raw text data from several varieties of Arabic and a morpholo...

The many differences between Dialectal Arabic and Modern Standard Arabic (MSA) pose a challenge to the majority of Arabic natural language processing tools, which are designed for MSA. In this paper, we retarget an existing state-of-the-art MSA morphological tagger to Egyptian Arabic (ARZ). Our evaluation demonstrates that our ARZ morphology tagger outperforms its MSA variant on ARZ input in te...

Natural language processing applications are based on the morphology part. So they should meet some criteria in order to satisfy the required functionality. Assessing and evaluating of Arabic morphological systems depend on the input words and resulted output according to a predefined criteria to measure and analyze given system in order to study its weakness and strength, trying to find an Ara...

Arabic script is naturally cursive and unconstrained and, as a result, an automatic recognition of its handwriting is a challenging problem. The analysis of Arabic script is further complicated in comparison to Latin script due to obligatory dots/stokes that are placed above or below most letters. In this paper, we introduce a new approach that performs online Arabic word recognition on a conti...

Arabic phonetics has been part of the study of Arabic language since the 7 th century CE. The great works by Al-Khali:l, "Kita:b al-'Ayn", and Si:bawayh, author of the first Arabic grammar book "al-kita:b" (i.e., "The Book") are the two cornerstones of this field. The early Arab grammarians knew phonetics quite well, although they mixed it with phonology, but interest in phonetics has remained ...

In this paper, we have designed and implemented a system for building an Automatic Lexicon for the Arabic language. Our Arabic Lexicon contains word specific information. These pieces of information include; morphological information such as the root (stem) of the word, its pattern and its affixes, the part-of-speech tag of the word, which classifies it as a noun, verb or particle; lexical attr...

Arabic language and writing are now facing a resurgence of international normative solutions that challenge most of their local or network based operating principles. Even if the multilingual digital coding solutions, especially those proposed by Unicode, have solved many difficulties of Arabic writing, the linguistic aspect is still in search of more adapted solutions. Terminology is one of th...

We present a limited speech translation system for English and colloquial Levantine Arabic, which we are currently developing as part of the DARPA Babylon program. The system is intended for question/answer communication between an English-speaking operator and an Arabic-speaking subject. It uses speech recognition to convert a spoken English question into text, and plays out a pre-recorded spe...

Modern Standard Arabic (MSA) is the formal language in most Arabic countries. Arabic Dialects (AD) or daily language differs from MSA especially in social media communication. However, most Arabic social media texts have mixed forms and many variations especially between MSA and AD. This paper aims to bridge the gap between MSA and AD by providing a framework for the translation of texts of soc...

Arabic is a Semitic language spoken by millions of people in 20 different countries. However, not much work has been done in the field of online dictionaries or lexical resources. WordNet is an example of a lexical resource that has not been yet developed to its full extent for Arabic. WordNet, a lexical database developed by Professor George Miller and his team at Princeton University, has see...