Formal Description of Arabic Syntactic Structure in the Framework of the Government and Binding Theory

Abstract

The research focus in our paper is twofold: (a) to examine the extent to which simple Arabic sentence structures comply with the Government and Binding Theory (GB), and (b) to implement a simple Arabic Context Free Grammar (CFG) parser to analyze input sentence structures to improve some Arabic Natural Language Processing (ANLP) Applications.Here we present a parser that employs Chomsky's Government and Binding (GB) theory to better understand the syntactic structure of Arabic sentences. We consider different simple word orders in Arabic and show how they are derived. We analyze different sentence orders including Subject-Verb-Object (SVO), Verb-Object-Subject (VOS), Verb-Subject-Object (VSO), nominal sentences, nominal sentences beginning with inna (and sisters) and question sentences. We tackle the analysis of the structures to develop syntactic rules for a fragment of Arabic grammar. We include two sets of rules: (1) rules on sentence structures that do not account for case and (2) rules on sentence structures that account for case of Noun Phrases (NPs). We present an implementation of the grammar rules in Prolog. The experiments revealed high accuracy in case assignment in Modern Standard Arabic (MSA) in the light of GB theory especially when the input sentences are tagged with identification of end cases.

Human-Informed Speakers and Interpreters Analysis in theWAWCorpus and an Automatic Method for Calculating Interpreters’ Décalage

“…Data Selection -The WAW Corpus: For all experiments and analysis we used the recordings and transcripts of conference speeches and of interpreters from the WAW corpus for the source language English and target Arabic. The WAW corpus is a conference interpreting corpus collected from three conferences which took place in Qatar in 2013-2014: WISE 2013 133) have as source language English, target Arabic, with very few (7) having source language Arabic and target English. The WAW corpus was collected in order to train the QCRI's 2 speech-to-speech machine translation system.…”

“…In fact longer décalage is generally to be avoided by interpreters as they should then keep more information in short-term memory and accuracy may significantly decrease (Lee, 2002). This is especially valid for interpreting between languages with highly different syntactic structures (Lee, 2002;Barik, 1975;Gile, 1997) such as English and Arabic (Bassam et al, 2014;Badr et al, 2009). Thus keeping décalage short can also be considered as an interpreting strategy.…”

Introducing linguistic transformation to improve translation memory retrieval Results of a professional translators’ survey for Spanish, French and Arabic

“…The analysis of empirical data indicates that the matching scores decrease between language pairs of the same language family such as ES-FR/FR-ES because of the transformations, but it also shows that Arabic as a source language faces other difficulties when it comes to translating into Spanish, where several segments have no matching. Arabic also registered lower matching percentage with MemoQ, which seems to have more difficulties with the word order transformation than SDL Trados despite that Modern Standard Arabic has a rich and flexible morphology in terms of word order (Bassam & al, 2017) and there are several possibilities of syntactic typology: Verb, Subject, Object (VSO), Subject, Verb, Object (SVO) and Verb, Object, Subject (VOS). For Spanish, the first results show that MemoQ has considerable difficulties when it comes to transform the active/passive voice and the substitution of a word by a synonym.…”

The Problem of Universal Grammar with Multiple Languages: Arabic, English, Russian as Case Study

“…The word order in Russian is not fixed; the sentence in the Russian language may be composed of a combination of the word order, that is to say, the place of the subject, the verb and object of the sentences can be changed without any change in the meaning of the sentences [18]. Flexibility in the Russian language means that the sentence admits the six-word order structures (SVO, SOV, VSO, VOS, OSV, and OVS) without any change in the meaning of the sentence.…”