Besides for its own merits, text classification (TC) has become a cornerstone in many applications. Work presented here is part of and a pre-requisite for a project we have overtaken to create a corpus for the Arabic text process. It is an attempt to create modules automatically that would help speed up the process of classification for any text categorization task. It also serves as a tool for...

The University of Maryland Researchers participated in both the Arabic-English Cross Language Information Retrieval (CLIR) and Video tracks of TREC-10. In the CLIR track, our goal was to explore effective monolingual Arabic IR techniques and effective query translation from English to Arabic for cross language IR. For the monolingual part, the use of the different index terms including words, s...

In this paper, we propose simple classifiers for printed Arabic characters based on statistical analysis. 109 printed Arabic character images are created for each one of transparent, simplified and traditional Arabic fonts. Images are preprocessed by the binarization and followed by sequence of morphological operations. A non-linear filter is applied on the thinned ridge map to extract terminat...

Despite of much work on TTS technologies and several TTS systems customized for Korean, current TTS systems output many errors in transliterating non-alphabetic symbols such as Arabic numerals and text symbols. This paper proposes TLAN (Transliteration Learner for Arabic-Numeral expressions) which can efficiently disambiguate the reading and meaning of Arabic Numeral Expressions (ANEs) in texts...

Morphological analysis of Arabic words allows decreasing the storage requirements of the Arabic dictionaries, more efficient encoding of diacritical Arabic text, faster spelling and efficient Optical character recognition. All these factors allow efficient storage and archival of multilingual digital libraries that include Arabic texts. This paper presents a lossless compression algorithm based...

We propose in this work a novel acoustic phonetic study for Arabic people suffering from language disabilities and non-native learners of Arabic language to classify Arabic continuous speech to pathological or healthy and to identify phonemes that pose pronunciation problems (case of pathological speeches). The main idea can be summarized in comparing between the phonetic model reference to Ara...

In this work we explore some challenges related to analysing one form of the Arabic language called Arabizi. Arabizi, a portmanteau of Araby-Englizi, meaning Arabic-English, is a digital trend in texting Non-Standard Arabic using Latin script. Arabizi users express their natural dialectal Arabic in text without following a unified orthography. We address the challenge of identifying Arabizi fro...

In this paper, we describe an extension to a hybrid machine translation system for handling dialect Arabic, using a decoding algorithm to normalize non-standard, spontaneous and dialectal Arabic into Modern Standard Arabic. We prove the feasibility of the approach by measuring and comparing machine translation results in terms of BLEU with and without the proposed approach. We show in our tests...