The differential effects of consonant and vowel diacritics in Arabic

Sami Boudelaa, Dennis Norris, Sachiko Kinoshita

Research output: Contribution to journalArticlepeer-review


Much recent research on the front end of visual word recognition has focused on how letters with and without diacritic marks are identified. In this study we report three masked priming letter match experiments which examine the processing of two types of diacritic marks in Arabic, a language/writing system rich in diacritics. Experiment 1 focused on diacritic dots that are obligatory and signal a phonemic contrast in consonants. The results showed an oft-replicated asymmetric diacritic priming pattern, namely, that for a target letter with a diacritic (e.g., ش, /$/), the prime without the diacritic (e.g., س, /s/) facilitated recognition almost as much as the identity prime (e.g., ش–ش= س–ش).; in contrast, a target without a diacritic is primed less strongly by the prime with the diacritic than by the identity prime (e.g., س–س < ش–س). Experiment 2 used vowel diacritics which also signal a phonemic contrast when present and collectively play the role of a morpheme, but are not obligatory and appear only in text for children or in the Quran. The results revealed a novel pattern in which both target letters with (e.g., سَ, /sa/) and without (e.g., س, /s/) vowel diacritics were equally facilitated by identity and related primes (e.g., س–سَ = سَ–سَ and سَ–س = س–س). Experiment 3 replicated these effects using a within-participant design. These results are discussed in light of current views of letter and diacritic processing.

Original languageEnglish
Article number104533
JournalJournal of Memory and Language
Publication statusPublished - Oct 2024


  • Arabic letters and words
  • Bayesian Reader-Noisy Channel model
  • Diacritics
  • Masked priming
  • Orthographic processing

ASJC Scopus subject areas

  • Neuropsychology and Physiological Psychology
  • Language and Linguistics
  • Experimental and Cognitive Psychology
  • Linguistics and Language
  • Artificial Intelligence


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