Does diacritics-based lexical disambiguation modulate word frequency, length, and predictability effects? An eye-movements investigation of processing Arabic diacritics.
Ehab W Hermena, Sana Bouamama, Simon P Liversedge and 1 more
PLoS ONE · 2021
doi:10.1371/journal.pone.0259987 (opens in a new tab)
We email you when a new notice or a question about this paper appears.
Abstract
In Arabic, a predominantly consonantal script that features a high incidence of lexical ambiguity (heterophonic homographs), glyph-like marks called diacritics supply vowel information that clarifies how each consonant should be pronounced, and thereby disambiguate the pronunciation of consonantal strings. Diacritics are typically omitted from print except in situations where a particular homograph is not sufficiently disambiguated by the surrounding context. In three experiments we investigated whether the presence of disambiguating diacritics on target homographs modulates word frequency, length, and predictability effects during reading. In all experiments, the subordinate representation of the target homographs was instantiated by the diacritics (in the diacritized conditions), and by the context subsequent to the target homographs. The results replicated the effects of word frequency (Experiment 1), word length (Experiment 2), and predictability (Experiment 3). However, there was no evidence that diacritics-based disambiguation modulated these effects in the current study. Rather, diacritized targets in all experiments attracted longer first pass and later (go past and/or total fixation count) processing. These costs are suggested to be a manifestation of the subordinate bias effect. Furthermore, in all experiments, the diacritics-based disambiguation facilitated later sentence processing, relative to when the diacritics were absent. The reported findings expand existing knowledge about processing of diacritics, their contribution towards lexical ambiguity resolution, and sentence processing.
Abstract licence: CC BY
Reads
Read by people on this page
None yet.
Checked or read by AI through naulon
None yet.
A person counts once a day per paper. We keep no cookie and no address: a reader is a hash that changes every day. Any month under five reads shows no number.
Are you an author?
Is this your paper?
Claim it to add your note and be paid when agents cite it. Free.