The Quranic Arabic Corpus (http://corpus.quran.com) is an annotated linguistic resource with multiple layers of annotation including morphological segmentation, part-of-speech tagging, and syntactic analysis using dependency grammar. The motivation behind this work is to produce a resource that enables further analysis of the Quran, the 1,400 year old central religious text of Islam. This paper...

We develop a framework for using the Natural Language Toolkit (NLTK) to parse Quranic Arabic sentences. This framework supports the construction of a treebank for the Holy Quran. The proposed model succeeds in parsing different Quranic chapters (Suras) in addition to Modern Standard Arabic (MSA) sentences. The availability of such parser will be useful in various natural language processing app...

The number of Free Online Machine Translation (FOMT) users witnessed a spectacular growth since 1994. FOMT systems change the aspects of machine translation (MT) and the mass translated materials using a wide range of natural languages and machine translation systems. Hundreds of millions of people use these FOMT systems to translate the holy Quran (Al-Qurʾān) verses from the Arabic language to...

Recitation of the Holy Quran with Tajweed is an essential activity as a Muslim. Reciting Quran correctly indicates the correct meaning of the words of Allah has been received from this significant resource among Muslims. That is why Muslims stress on the Quranic Education since in the early age. It is important to pronounce the letter correctly based on its characteristics as well as the articu...

The Quranic Arabic Corpus (http://corpus.quran.com) is a collaboratively constructed linguistic resource initiated at the University of Leeds, with multiple layers of annotation including part-of-speech tagging, morphological segmentation (Dukes & Habash, 2010) and syntactic analysis using dependency grammar (Dukes & Buckwalter, 2010). The motivation behind this work is to produce a resource th...

Part Of Speech (POS) tagging forms the important preprocessing step in many of the natural language processing applications such as text summarization, question answering and information retrieval system. It is the process of classifying every word in a given context to its appropriate part of speech. Different POS tagging techniques in the literature have been developed and experimented. Curre...

We present a formalized rhyme function for machine approximation of human rhyme. Words are represented as sequences of phonemic features that facilitate the use of alignment mechanisms to compute different types of phonemic similarities between words. The rhyme function computes a weighted hierarchical combination of these similarities, with the weights determined using an evolutionary approach...

Previous research has been equivocal about whether deaf children can develop rhyme awareness. The current experiment investigates the rhyme skills of deaf children (mean age 11 years). Deaf children’s ability to make rhyme judgements was above chance, but poorer than that of their reading matched hearing controls. We conclude that deaf children do have a degree of rhyme awareness. We also discu...