In TREC 2002 the Berkeley group participated only in the English-Arabic cross-language retrieval (CLIR) track. One Arabic monolingual run and three English-Arabic cross-language runs were submitted. Our approach to the crosslanguage retrieval was to translate the English topics into Arabic using online English-Arabic machine translation systems. The four official runs are named as BKYMON, BKYCL...

! The Judeo-Arabic languages comprise a set of dialects spoken and written by Jewish communities living in Arab countries, mainly during the middle ages. Judeo-Arabic is typically written in Hebrew letters, enriched with various diacritic marks. The Judeo-Arabic spoken and written by any particular Jewish community is similar to the Arabic dialect used by their local Muslim community. In additi...

A comparison of F0 alignment values was carried out for three Arabic dialects (Moroccan Arabic, Kuwaiti Arabic and Yemeni Arabic) using five speakers from each dialect. Clear differences found in alignment enable separation of Moroccan Arabic from the two other dialects: a) values of the F0 valley differed significantly, with Moroccan Arabic showing a later synchronisation than Kuwaiti Arabic a...

Arabic Grammar, Arabic Upper Model, Arabic Gemeration. Arabic has had wellestablished theoretical studies for more than 1000 years. However, If Arabic is compared with other languages, it has received much less modern computational interest. The aim of this research work is to try to make use of some of the Arabic linguistic theories and adapt them to be used in machine processing. To start wit...

In the past several years, Arabic Information Retrieval (IR) has garnered significant attention. The main research interests have focused on retrieval of formal language, mostly in the news domain, with ad hoc retrieval, OCR document retrieval, and cross-language retrieval. The literature on other aspects of retrieval continues to be sparse or non-existent, though some of these aspects have bee...

Most tools and resources developed for natural language processing of Arabic are designed for Modern Standard Arabic (MSA) and perform terribly on Arabic dialects, such as Egyptian Arabic. Egyptian Arabic differs from MSA phonologically, morphologically and lexically and has no standardized orthography. We present a linguistically accurate, large-scale morphological analyzer for Egyptian Arabic...

This book provides system developers and researchers in natural language processing and computational linguistics with the necessary background information for working with the Arabic language. The goal is to introduce Arabic linguistic phenomena and review the state-of-the-art in Arabic processing. The book discusses Arabic script, phonology, orthography, morphology, syntax and semantics, with...

Most tools and resources developed for natural language processing of Arabic are designed for Modern Standard Arabic (MSA) and perform terribly on Arabic dialects, such as Egyptian Arabic. Egyptian Arabic differs from MSA phonologically, morphologically and lexically and has no standardized orthography. We present a linguistically accurate, large-scale morphological analyzer for Egyptian Arabic...

This work presents a system for Automatic Arabic punctuation marks. Existing approaches for automatic punctuation marks do not provide suitable performance for and do not satisfy user interests in Arabic texts. The importance and rising need to automate the correct insertion of punctuation marks in Arabic texts led to a need of specific analysis of the Arabic language to introduce approaches th...