Residual-based approach for authenticating pattern of multi-style diacritical Arabic texts

Hakak, Saqib; Kamsin, Amirrudin; Palaiahnakote, Shivakumara; Tayan, Omar; Mohd. Yamani Idna Idris; Zuhaili Abukhir, Khir

Abstract

Arabic script is highly sensitive to changes in meaning with respect to the accurate arrangement of diacritics and other related symbols. The most sensitive Arabic text available online is the Digital Qur’an, the sacred book of Revelation in Islam that all Muslims including non-Arabs recite as part of their worship. Due to the different characteristics of the Arabic letters like diacritics (punctuation symbols), kashida (extended letters) and other symbols, it is written and available in different styles like Kufi, Naskh, Thuluth, Uthmani, etc. As social media has become part of our daily life, posting downloaded Qur’anic verses from the web is common. This leads to the problem of authenticating the selected Qur’anic passages available in different styles. This paper presents a residual approach for authenticating Uthmani and plain Qur’an verses using one common database. Residual (difference) is obtained by analyzing the differences between Uthmani and plain Quranic styles using XOR operation. Based on predefined data, the proposed approach converts Uthmani text into plain text. Furthermore, we propose to use the Tuned BM algorithm (BMT) exact pattern matching algorithm to verify the substituted Uthmani verse with a given database of plain Qur’anic style. Experimental results show that the proposed approach is useful and effective in authenticating multi-style texts of the Qur’an with 87.1% accuracy.

Citation

Hakak, S., Kamsin, A., Palaiahnakote, S., Tayan, O., Mohd. Yamani Idna Idris, & Zuhaili Abukhir, K. (2018). Residual-based approach for authenticating pattern of multi-style diacritical Arabic texts. PloS one, https://doi.org/10.1371/journal.pone.0198284

• Journal Article Type: Article
• Acceptance Date: May 13, 2018
• Publication Date: Jun 20, 2018
• Deposit Date: Nov 15, 2024
• Publicly Available Date: Nov 19, 2024
• Journal: PLoS ONE
• Print ISSN: 1932-6203
• Electronic ISSN: 1932-6203
• Publisher: Public Library of Science
• Peer Reviewed: Peer Reviewed
• DOI: https://doi.org/10.1371/journal.pone.0198284