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...

This paper investigates speech timing in Modern Standard Arabic (MSA) of Algerian speakers in order to situate their Arabic language between stressed-timed and syllable-timed languages. We extracted first all duration measurements from recordings taken from sound voice bank ALGASD (ALGerian Arabic Speech Database) and after computed durations with using recently interesting rhythmic approaches.

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...

Algerian Arabic is an Arabic dialect spoken in Algeria characterized by the absence of writing resources and standardization, hence it is considered as an under-resourced language. It differs from Modern Standard Arabic on all levels of linguistic representation, from phonology and morphology to lexicon and syntax. In this paper, we present a conventional orthography for Algerian Arabic, follow...

Building a system to extract Arabic named entities is a complex task due to the ambiguity and structure of Arabic text. Previous approaches that have tackled the problem of Arabic named entity recognition relied heavily on Arabic parsers and taggers combined with a huge set of gazetteers and sometimes large training sets to solve the ambiguity problem. But while these approaches are applicable ...

Dialectal Arabic speech recognition is a difficult problem and is relatively less studied. In this paper, we propose a cross-dialectal Gaussian mixture model training criteria to transfer knowledge from one domain to the other by data sharing. Specifically, phone classification experiments on West Point Modern Standard Arabic Speech corpus and Babylon Levantine Arabic Speech corpus demonstrate ...