Tools for Arabic Natural Language Processing: a case study in qalqalah prosody

In this paper, we focus on the prosodic effect of qalqalah or "vibration" applied to a subset of Arabic consonants under certain constraints during correct Qur'anic recitation or taǧwīd, using our Boundary-Annotated Qur’an dataset of 77430 words (Brierley et al 2012; Sawalha et al 2014). These qalqalah events are rule-governed and are signified orthographically in the Arabic script. Hence they can be given abstract definition in the form of regular expressions and thus located and collected automatically. High frequency qalqalah content words are also found to be statistically significant discriminators or keywords when comparing Meccan and Medinan chapters in the Qur'an using a state-of-the-art Visual Analytics toolkit: Semantic Pathways. Thus we hypothesise that qalqalah prosody is one way of highlighting salient items in the text. Finally, we implement Arabic transcription technology (Brierley et al under review; Sawalha et al forthcoming) to create a qalqalah pronunciation guide where each word is transcribed phonetically in IPA and mapped to its chapter-verse ID. This is funded research under the EPSRC "Working Together" theme.