Prefixed Nouns and Verbs in Arabic: Evidence for Dual-route Processing in Auditory Word Recognition

The process of accessing and retrieving the morphological components of complex words during word recognition has led to the development of various models that explain morphological representation and processing. This area of research is particularly significant in the context of Arabic, where it has been suggested that lexical processing predominantly relies on root-based obligatory morphological decomposition, as opposed to stem-based processing. To investigate this proposal, we conducted an experiment focusing on morphologically complex prefixed words. These words were carefully matched for surface and stem frequencies, allowing us to isolate the variable of root type frequency, or family size, to observe its specific effects. We analyzed the impact of root type frequency on response times for lexical decisions concerning spoken prefixed nouns and verbs in Arabic. Our findings revealed that response times for lexical decisions were significantly influenced by root type frequency, but only for prefixed nouns. This suggests that the proposed model of root-based obligatory morphological decomposition may not be universally applicable to all types of prefixed words in Arabic. Instead, these results indicate a need for a more nuanced understanding of morphological processing, supporting dual-mechanism approaches over single-mechanism theories. This research contributes to the ongoing discourse on morphological processing in language, particularly highlighting the complexities involved in recognizing morphologically rich languages like Arabic.

Authors

Institutions

Publication Details

Journal
Forum for Linguistic Studies
Published
2024-12-17
DOI
https://doi.org/10.30564/fls.v7i1.7861
Primary Topic
Language, Linguistics, Cultural Analysis
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Prefixed Nouns and Verbs in Arabic: Evidence for Dual-route Processing in Auditory Word Recognition

Faisal Aljasser
Forum for Linguistic Studies
Language, Linguistics, Cultural Analysis
article

Prefixed Nouns and Verbs in Arabic: Evidence for Dual-route Processing in Auditory Word Recognition

Faisal Aljasser
article en

Abstract

The process of accessing and retrieving the morphological components of complex words during word recognition has led to the development of various models that explain morphological representation and processing. This area of research is particularly significant in the context of Arabic, where it has been suggested that lexical processing predominantly relies on root-based obligatory morphological decomposition, as opposed to stem-based processing. To investigate this proposal, we conducted an experiment focusing on morphologically complex prefixed words. These words were carefully matched for surface and stem frequencies, allowing us to isolate the variable of root type frequency, or family size, to observe its specific effects. We analyzed the impact of root type frequency on response times for lexical decisions concerning spoken prefixed nouns and verbs in Arabic. Our findings revealed that response times for lexical decisions were significantly influenced by root type frequency, but only for prefixed nouns. This suggests that the proposed model of root-based obligatory morphological decomposition may not be universally applicable to all types of prefixed words in Arabic. Instead, these results indicate a need for a more nuanced understanding of morphological processing, supporting dual-mechanism approaches over single-mechanism theories. This research contributes to the ongoing discourse on morphological processing in language, particularly highlighting the complexities involved in recognizing morphologically rich languages like Arabic.

Forum for Linguistic StudiesVol. 7(1)
Qassim University (SA), Buraydah Colleges (SA)
Qassim University
Quality Education
Openalex Percentile: Top 58%
Language, Linguistics, Cultural Analysis
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.