Arabic Dialects Research Database
A trusted, searchable reference for publications on Arabic dialects.
Who I Am
Dr. Muhammad Alzaidi is an associate professor of linguistics and AI-developer specializing in Arabic linguistics, dialectology, and computational tools. Founder of ظ.ai, he builds open-access databases and smart digital labs (e.g., ArPhon, Vowel AI, Citation Builder) to advance research in Arabic language and speech technology.
📧 Email: malzaidi1@ksu.edu.sa
🌐 Website: faculty.ksu.edu.sa/ar/malzaidi1/cv.
Why /ðˤ/?
We chose “ðˤ” to signal a uniquely Arabic identity. The classical linguist Abū ʿAmr ʿUthmān ibn Saʿīd al-Dānī (371–444 AH), in his treatise “The Difference between Ḍād and ðˤ”, reports a consensus among scholars that the letter /ðˤ/ is exclusive to Arabic among the world’s languages. Because of its rarity, it appears only in roughly a hundred words across the lexicon. That distinctiveness makes /ðˤ/ an emblem of Arabic phonology and scholarship; hence its adoption as the name of our platform dedicated to rigorous, well-documented Arabic research.
Vision & Mission
Our vision: toward a recognized research standard.
Our mission: provide an open platform for reliable data, smart tools, and digital labs with clear documentation/citation standards for reproducible, academically trusted knowledge.
Tools
Smart AI Reference Builder
Smart AI Reference Builder: A smart tool designed for linguists and NLP researchers.
AR-PhonoLab
AR-PhonoLab: A free, open-access lab for analyzing the sounds and prosody of Arabic and its dialects.
Arabic Speech Annotator
Arabic Speech Annotator: Automate speech segmentation and phonetic analysis with AI.
MorphoSyntax Explorer
MorphoSyntax Explorer: Unlock the structure of Arabic words and sentences.
Vowel AI Tool
Vowel AI blends phonetic theory with machine learning to normalize and visualize acoustic features and use supervised models to classify vowels and uncover subtle patterns; bridging experimental phonetics and computational phonology.
ArPhon Tool
ArPhon Tool: instant, research-grade insights for Arabic speech, dialect-aware F0, intensity, and formants; with stunning, publication-ready visuals.
Journal_Suggest Tool
An Arabic-first, reliable journal AI finder: semantic matching, indexing badges, and authoritative links to help you pick reliable venues.
How to Get an Invite Code
To get an invite code, please email Dr. Muhammad Alzaidi at malzaidi1@ksu.edu.sa.
Frequently Asked Questions
Yes when DOI/publisher page is available; use “Copy Citation” and validate formatting; refer to the publisher if unsure.
From the original source when available; otherwise a carefully prepared AR/EN summary is provided. Guiding comments are reviewed periodically for quality.
Use the “Report Issue” button; your note arrives with links/IDs so we can correct the record.
Copyright preserved by ðˤ -
Dr. Muhammad Alzaidi