OBJECTIVE The aim of this study was to develop an Arabic articulation test using familiar and visually transparent words in order to be used as a criterion for comparing phonemes of both normal and phonologically disordered Arabic-speaking children. MATERIAL AND METHODS A picture-naming test was designed for the Mansoura Arabic Articulation Test (MAAT) to elicit spontaneous single-word respon...

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...

This paper summarizes some techniques proposed for off-line Arabic word recognition. The point of view developed here concerns the human reading favoring an interactive mechanism between global memorization and local checking making easier the recognition of complex scripts as Arabic. According to this consideration, some specific papers are analyzed and their strategies commented.

This paper describes our efforts to build an Arabic ASR system with web-crawled resources. We first describe the processing done to handle Arabic text in general and more particularly to cope with the high number of different phonetic transcriptions associated to a typical Arabic word. Then, we present our experiments to build acoustic models using only audio data found in the web, in particula...

Segmentation of clitics has been shown to improve accuracy on a variety of Arabic NLP tasks. However, state-of-the-art Arabic word segmenters are either limited to formal Modern Standard Arabic, performing poorly on Arabic text featuring dialectal vocabulary and grammar, or rely on linguistic knowledge that is hand-tuned for each dialect. We extend an existing MSA segmenter with a simple domain...

Text readability refers to the ability of the reader to understand and comprehend a given text. In this research, we present our approach to develop an automatic readability index for the Arabic language: Automatic Arabic Readability Index (AARI), using factor analysis. Our results are based on more than 1196 Arabic texts extracted from the Jordanian curriculum in the subjects of: Arabic langua...

No satisfactory solutions are yet available for the offline recognition of handwritten cursive words, including the words of Arabic text. Word matching algorithms can greatly improve the OCR output when recognizing words of known and limited vocabulary. This paper describes the word matching algorithm used in the JU-OCR2 optical character recognition system of handwritten Arabic words. This sys...

A crucial question in the domain of visual word recognition is whether letter similarity plays a role in the early stages of visual word processing. Here we focused on Arabic because in this language there are various groups of letters that share the same basic shape and only differ in the number/location of diacritical points. We conducted a masked priming lexical decision experiment in which ...

We investigate different types of features for language modeling in Arabic automatic speech recognition. While much effort in language modeling research has been directed at designing better models or smoothing techniques for n-gram language models, in this paper we take the approach of augmenting the context in the n-gram model with different sources of information. We start by adding word cla...

Segmenting arabic manuscripts into text-lines and words is an important step to make recognition systems more efficient and accurate. The major problem making this task crucial is the word extraction process: first, words are often a succession of sub-words where the space value between these sub-words do not respect any rules. Second, the presence of connections even between non adjacent sub-w...