Character recognition for Arabic texts poses a twofold challenge, segmenting words into letters and identifying the individual letters. We propose a method that combines the two tasks, using a grid of SIFT descriptors as features for classification of letters. Each word is scanned with increasing window sizes; segmentation points are set where the classifier achieves maximal confidence. Using t...

Machine translation engines draw on various types of databases. This paper is concerned with Arabic as a source or target language, and focuses on lexical databases. The non-concatenative nature of Arabic morphology, the complex structure of Arabic word-forms, and the general use of vowel-free writing present a real challenge to NLP developers. We show here how and why a stem-grounded lexical d...

Users are still waiting for accurate optical character recognition solutions for Arabic handwritten scripts. This research explores best sets of feature extraction techniques and studies the accuracy of well-known classifiers for Arabic letters. Depending on their position in the word, Arabic letters are drawn in four forms: Isolated, Initial, Medial, and Final. The principal component analysis...

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...

This paper presents a case-study of work done by Applied Language Solutions (ALS) for a large social networking provider who claim to have built the world’s first multi-language social network, where Internet users from all over the world can communicate in languages that are available in the system. In an initial phase, the social networking provider contracted ALS to build Machine Translation...

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...

In this paper, a supervised learning technique for extracting keyphrases of Arabic documents is presented. The extractor is supplied with linguistic knowledge to enhance its efficiency instead of relying only on statistical information such as term frequency and distance. During analysis, an annotated Arabic corpus is used to extract the required lexical features of the document words. The know...

The noun plural system in Modern Standard Arabic lies at a nexus of critical issues in morphological learnability. The suffixing "sound" plural competes with as many as 31 non-concatenative "broken" plural patterns. Our computational analysis of singular-plural pairs in the Corpus of Contemporary Arabic explores what types of linguistic information are statistically relevant to morphological ge...