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- Volume 1, Issue 2, 2025
Arabic Linguistics - Volume 1, Issue 2, 2025
Volume 1, Issue 2, 2025
Edited by Reem Khamis (Long Island University, Brooklyn) & Mira Goral (Lehman College, City University of New York)
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No effect of L1 on learners’ sensitivity to noun-adjective agreement patterns in an explicit judgment task
Author(s): Halimah Alalawi and Cynthia Lukyanenkopp.: 147–167 (21)More LessAbstractWe investigated the role of cross-linguistic influence of learners’ first language on their L2 acquisition of Modern Standard Arabic (MSA) by testing L2 learners’ perception of MSA noun-adjective agreement and comparing learners who have noun-adjective agreement in their L1 to those who do not. In a Grammaticality Judgment task, participants read MSA sentences that contained either grammatical or ungrammatical noun-adjective agreement patterns. Native speakers were more sensitive to grammaticality than learners were, and learners were better than chance. However, we found no reliable effects of L1 agreement. This finding aligns with prior results suggesting that cross-linguistic transfer is less likely in offline than in online tasks and suggests either that late L2 learners have sensitivity to the new grammar regardless of the patterns of their L1 or that the alignment between languages necessary for facilitation is more detailed than the simple presence or absence of agreement.
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Acquisition of noun plurals in Egyptian‑Arabic speaking children
Author(s): Samantha Ghali, Heba Salama and Mira Goralpp.: 168–187 (20)More LessAbstractResearch investigating Arabic-speaking children’s acquisition of noun plurals is emerging. Researchers hypothesize that, consistent with a single-route model of morphological processing, children rely more on concatenative than on non-concatenative morphological processes. This is expected because processes of affixation require few morphological changes and fewer cognitive resources than non-concatenative processes, which necessitate multiple morphological changes within a word. However, other evidence suggests that children begin to acquire non-concatenative processes at the same time as concatenative processes. We performed a corpus analysis of Egyptian Arabic-speaking children’s use of noun plurals (ages 1;7–3;7). Accuracy rates, type-token ratios, and error patterns were examined. We found that the children used both non-concatenative and concatenative morphological processes, and had overall low rates of morphological errors. Findings replicate previous work and contribute novel results to the literature. Our preliminary results support dual-route processing models of inflectional morphology.
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Modeling distance-based variable sibilant harmony in Moroccan Arabic with a MaxEnt grammar
Author(s): Ali Nirhechepp.: 188–215 (28)More LessAbstractThe aim of this study is to examine the variable patterns of regressive sibilant harmony in Moroccan Arabic. This process is triggered by the palatal fricative [ʒ], and targets the alveolar fricatives [z] and [s], changing them to [ʒ] and [ʃ] respectively (Harrell, 1962; Heath, 1987, 2002). This paper examines how factors such as the distance between harmonizing segments, voicing of the target segment, and morphological complexity influence the likelihood of harmonization. The findings from an experimental study reveal that the distance between the two harmonizing sibilants significantly influences harmonization, with a shorter distance indicating a higher likelihood of harmonization. Moreover, while voicing of the target sound appears to affect harmonization, a closer examination of the experimental results attributes this effect to the exceptional behavior of some words whose harmonizing sound happens to be [s]. The study uses Maximum Entropy grammar (Goldwater & Johnson, 2003) to learn the variability in applying harmonization. The analysis incorporates Agreement-by-Correspondence constraints (Rose & Walker, 2000, 2004) to account for the observed distance effects and lexically-indexed constraints (Pater, 2000, 2009) to capture the exceptional behavior of certain lexical items that do not follow the general trends.
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When prosody meets syntax in Hijazi Arabic gapping
Author(s): Aisha Fuddah, Hammad Alshammari and Hanyong Parkpp.: 216–239 (24)More LessAbstractThis study is the first to examine how speakers deal with structural ambiguity arising from elliptical gapping constructions like Shahad saw Aahad at the library and Samar at the mall, which may be interpreted with a gapping structure (both Shahad and Samar saw Aahad) or a non-gapping structure (Shahad saw both Aahad and Samar). The central question of this study explores the role that prosody plays in resolving such ambiguity in Hijazi Arabic. Analysis of productions from 24 native speakers reveals that various prosodic cues, such as mean F0, max F0, intensity, and excursion size, are used for unambiguous sentences, while pause occurrence, pause duration, and pitch accents are additionally utilised as disambiguation cues when ambiguity is recognised. The study reveals that speakers phonetically reflect syntactic structural differences in ambiguous sentences, particularly in relation to gapping. This distinction becomes more apparent when speakers are aware of ambiguity.
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Ellipsis in Arabic
Author(s): Muhammad S. Abdo, Dr. Damir Cavar, Billy Dickson and Dr. Attia Youseifpp.: 240–263 (24)More LessAbstractThis paper introduces the Hoosiers Arabic Ellipsis Corpus, a novel dataset targeting syntactic ellipsis in Arabic. Addressing the significant challenge ellipsis poses to natural language processing (NLP) technologies, the Hoosiers Arabic Ellipsis Corpus leverages the Corpus Query Language (CQL) to extract ellipsis instances from the ArTenTen corpus. To the best of our knowledge, this is the first comprehensive dataset of its kind, filling a critical gap in resources for Arabic, which remains under-resourced in NLP studies. We evaluate the corpus through three computational experiments: detecting sentences with ellipsis, predicting the location of elided elements, and generating missing words using state-of-the-art large language models (LLMs). Results demonstrate that few-shot prompting significantly improves LLM performance, with Gemini 2.5 Pro achieving the highest accuracy in ellipsis detection (95.6%). However, LLMs struggled with precisely locating and reconstructing elided elements. The findings highlight the challenges of ellipsis processing in Arabic and point to the need for larger, more balanced datasets and further refinement of NLP models to handle structural inference.
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The uncommonness of rāħ in Egyptian Arabic
Author(s): Michael Whitepp.: 264–279 (16)More LessAbstractEgyptian Arabic contains a semantically bleached verb rāħ whose functions have been thoroughly studied and identified; however, the motivation for its use remains unclear. Current theories about its motivations have resulted in a long list of seemingly disparate functions which cannot explain its high frequency within narratives or its occurrence outside of them. The theory of foregrounding offers a possible motivation for rāħ’s pattern of use. Identifying rāħ as a foregrounding device would require that its use either violate a grammatical rule or deviate from the norm. I will argue the latter by presenting corpus-based data which suggests that rāħ’s frequency is uncommon in narratives when compared to its use in daily Egyptian speech. The data will also show that rāħ’s frequency in narratives is not such that it has become the norm.
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