Arabic has a very complex morphological system, though a very structured one. Character patterns are often indicative of word class and word segmentation. In this paper, we e xplore a novel approach to Arabic word segmentation and part-of-speech tagging relying on character information. The approach is lexicon-free and does not require any morphological analysis, eliminat ing the factor of dict...

The limited coverage of available Arabic language lexicons causes a serious challenge in Arabic cross language information retrieval. Translation in cross language information retrieval consists of assigning one of the semantic representation terms in the target language to the intended query. Despite the problem of the completeness of the dictionary, we also face the problem of which one of th...

Morphological analysis and disambiguation are crucial stages in a variety of natural language processing applications such as machine translation, especially when languages with complex morphology are concerned such as Arabic. Arabic is a highly flexional language, in that, the same root can lead to various forms according to its context. In this paper, we present a system which disambiguates t...

We carried out a masked priming lexical decision experiment to study whether visual letter similarity plays a role during the initial phases of word processing in young readers of Arabic (fifth graders). Arabic is ideally suited to test these effects because most Arabic letters share their basic shape with at least one other letter and differ only in the number/position of diacritical points (e...

We investigated whether the mental representation of numbers is abstract amodal or modality-dependent. Subjects verified simple additions. In an event-related potential (ERP) experiment, subjects added an Arabic digit (S2) to a preceding number (S1) offsetting 3 s before S2. S1 was either a visually shown Arabic digit, a written number word or an acoustically presented number word. In a behavio...

Most of the actual research in writing recognition focuses on speci ̄c applications where the vocabulary is relatively small. Many applications can be opened up when handling with large vocabulary. In this paper, we studied the classi ̄er collaboration interest for the recognition of a large vocabulary of arabic words. The proposed approach is based on three classi ̄ers, named Transparent Neuronal...

Arabic Sign Language (ArSL) is the native language for the Arab deaf community. ArSL allows deaf people to communicate among themselves and with non-deaf people around them to express their needs, thoughts and feelings. Opposite to spoken languages, Sign Language (SL) depends on hands and facial expression to express the thought instead of sounds. In recent years, interest in translating sign l...

The Linguistic Data Consortium and Georgetown University Press are collaborating to create updated editions of bilingual dictionaries that had originally been published in the 1960’s for English-speaking learners of Moroccan, Syrian and Iraqi Arabic. In their first editions, these dictionaries used ad hoc Latin-alphabet orthography for each colloquial Arabic dialect, but adopted some properties...

Arabic morphology poses special challenges to computational natural language processing systems. Its rich morphology and the highly complex word formation process of roots and patterns make computational approaches to Arabic very challenging. In this paper we present an approach for morphological analysis and generation of Modern Standard Arabic (MSA). Our approach is based on Arabic morphologi...

Electronic Document Management (EDM) technology is being widely adopted as it makes for the efficient routing and retrieval of documents. Optical Character Recognition (OCR) is an important front end for such technology. Excellent OCR now exists for Latin based languages, but there are few systems that read Arabic, which limits the penetration of EDM into Arabicspeaking countries. In developing...