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Vowel unpredictability in Hijazi Arabic monosyllabic verbs

Paper · 2020 · Honaida Ahyad and Michael Becker

Summary

This study asks whether the imperfective vowel of monosyllabic verbs in Urban Hijazi Arabic is purely lexical or partly predictable from the root consonants. The first author, a native speaker, went through every two-consonant combination in the language, and two more speakers checked the result. The final lexicon has 238 monosyllabic verbs. A logistic regression on this lexicon shows that emphatic (pharyngealized) consonants interact with vowel length. With short vowels, emphatics favour back [u]. With long vowels, they favour front [ii]. A nonce-verb task with 104 participants showed that speakers extend both trends to novel forms. The authors model the pattern with the Minimal Generalization Learner (MGL), which learns probabilistic rules from perfective–imperfective surface pairs. Its predictions correlate significantly with speakers' choices. The authors conclude that Arabic lexical entries must give access to vowels and consonants together. Roots made only of consonants cannot explain how speakers generalize these consonant–vowel links.

Key points

  • The lexicon contains 133 short-vowel ("doubled") verbs and 105 long-vowel ("hollow") verbs. Imperfective [u] appears in 82% of the short-vowel verbs. Long-vowel verbs split roughly evenly between [ii] and [uu], and only 4 take [aa].
  • Emphatics raise the rate of [u] in short-vowel verbs from 77% to 97%. They lower the rate of [uu] in long-vowel verbs from 56% to 32%. The emphatic × length interaction is significant (β = –3.34, p < .005), and emphatics alone have no significant main effect.
  • The effect is also present in the 603 disyllabic measure I verbs: imperfective [u] occurs in 31% of verbs without an emphatic and 50% of verbs with one.
  • A comparison with Modern Standard Arabic and Palestinian shows the same direction (emphatic → short [u]) in all three varieties. Palestinian shows the largest effect, and Modern Standard Arabic shows the smallest.
  • MGL rules trained on perfective→imperfective pairs predicted the nonce-word responses well. The authors note that MGL handles only one pair of morphological categories at a time.

Interesting ideas

  • I1. The lexicon was built by listing every possible consonant pair and having native speakers mark which ones exist as verbs, which yields a complete inventory instead of a sample.
  • I2. Nonce words separate a pattern that speakers actively generalize from a pattern that is only a statistical fact about stored items.
  • I3. MGL builds explicit, scored rules from paired surface forms and applies them probabilistically, so every prediction can be traced back to a rule.
  • I4. Centring binary predictors before fitting the regression makes the main effects interpretable even when a strong interaction is present.
  • I5. The authors argue that naturalness predicts the direction of an effect, while its strength has to be learned separately for each language variety.

For Mova

How these ideas could serve Mova, our small open language model — its files, stages and tests:

  • I1 (tokens): We could generate all candidate stem or affix shapes and have an LLM teacher or human reviewer confirm which exist, giving a coverage check for the morphology lexicon.
  • I2 (learn): We could test the morphology and lemma rules on invented verbs; if a rule fires only on known words, it is memorization rather than generalization.
  • I3 (tokens): Inflecting or lemmatizing unknown English words could use reliability-weighted minimal-generalization rules learned from lemma–form pairs, with the winning rule shown as the explanation.
  • I4 (learn): When we analyse how parser errors depend on combined factors such as genre × construction, centred coding prevents a main effect from being misread when it is really driven by the interaction.
  • I5 (tree): UD dialect conversion could use linguistic priors to set the direction of a mapping and estimate its weights from each treebank, rather than hard-coding one strength for all of them.

Our summary of the paper, in our own words — not its text. The work belongs to its authors; read it at the links above.

 Institutions

🎓University of Massachusetts AmherstAmherst Center · United States67 works · 64,591 citations🎓Stony Brook UniversityStony Brook · United States27 works · 2,057 citations

📚 Shelves 4 Arts and Humanities · 9,296 works Language and Linguistics · 9,206 works Psychology · 798 works Experimental and Cognitive Psychology · 463 works

🧭 Topics 1 Semitic languages · 1,484 works

Cite

Cite as Honaida Ahyad and Michael Becker. 2020. Vowel unpredictability in Hijazi Arabic monosyllabic verbs. Glossa: a journal of general linguistics.

The paper itself, not this page. BibTeX from the library's record of the work. DOI 10.5334/gjgl.814

@article{ahyad2020vowel,
  title = {{Vowel unpredictability in Hijazi Arabic monosyllabic verbs}},
  author = {Honaida Ahyad and Michael Becker},
  journal = {Glossa: a journal of general linguistics},
  year = {2020},
  doi = {10.5334/gjgl.814},
  url = {https://doi.org/10.5334/gjgl.814}
}

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  32. How to cite this article: Ahyad, Honaida and Michael Becker. 2020. Vowel unpredictability in Hijazi Arabic monosyllabic verbs. Glossa: a journal of general linguistics 5(1): 32. 1–18. DOI: https://doi.org/10.5334/gjgl.814 ↗ our card
  33. Submitted: 21 September 2018 find
  34. Copyright: © 2020 The Author(s). This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International License (CC-BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. See http://creativecommons.org/licenses/by/4.0/. Glossa: a journal of general linguistics is a peer-reviewed open access journal published by Ubiquity Press. OPEN ACCESS ↗

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