Urdu is a challenging language because of, first, its Perso-Arabic script and second, its morphological system having inherent grammatical forms and vocabulary of Arabic, Persian and the native languages of South Asia. This paper describes an implementation of the Urdu language as a software API, and we deal with orthography, morphology and the extraction of the lexicon. The morphology is imple...

The Universal Networking Language (UNL) is an artificial language that can replicate human language functions in cyberspace in terms of hyper semantic networks. This paper aims to: a) design a reference grammar capable of dealing with the basic linguistic structures in order to act as a test-bed in automating translation between English and Arabic in both directions through UNL; b) evaluate the...

In this paper, we describe our system HASP-2015 (Hybrid Arabic Spelling and Punctuation Corrector) in which we introduce significant improvements over our previous version HASP-2014 and with which we participated in the QALB2015 Second Shared Task on Arabic Error Correction. Our system utilizes probabilistic information on errors and their possible corrections in the training data and combine t...

In this paper, we present a method to employ target-side syntactic contextual information in a Hierarchical Phrase-Based system. Our method uses Combinatory Categorial Grammar (CCG) to annotate training data with labels that represent the left and right syntactic context of target-side phrases. These labels are then used to assign labels to nonterminals in hierarchical rules. CCG-based contextu...

Phrase re-ordering is a well-known obstacle to robust machine translation for language pairs with significantly different word orderings. For Arabic-English, two languages that usually differ in the ordering of subject and verb, the subject and its modifiers must be accurately moved to produce a grammatical translation. This operation requires more than base phrase chunking and often defies cur...

Translation is the activity producing a source language message with closest and natural equivalent to recipient's language, both in terms of meaning style. The translation process requires grammatical lexical adjustments evade unusual structures language. activities are not only done by humans. With advancement technology, electronic tools have emerged such as Google Translate translate parts ...

Urdu is a challenging language because of, first, its Perso-Arabic script, second, its morphological system having inherent grammatical forms and vocabulary of Arabic, Persian and the native languages of South Asia and third, its pragmatically neutral constituent order (SOV Subject Object Verb). Today, the state of art technology to write grammars (morphology + syntax) is to use specialpurpose ...

Inference plays an important role in the learning process and it can lead to a rapid acquisition of a second language. When learning a non-native language i.e., a critical language like Arabic, the students depend on the teacher’s support most of the time to learn new concepts. The students focus on memorizing the new vocabulary and stress on learning all the grammatical rules. Hence, the stude...