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Templaticity Effects on Differential Processing of Consonants and Vowels

Paper · 2019 · Maya L. Barzilai

Summary

The study asks why consonants and vowels behave differently in short-term memory across languages. English speakers usually recall vowel differences better than consonant differences in immediate serial recall (ISR). Kissling (2012) found that Arabic speakers recall both equally well. Two explanations compete. One is Arabic's templatic morphology, in which consonantal roots carry lexical meaning. The other is its abjad script, which omits short vowels. To separate them, Barzilai added Amharic. Amharic shares templatic morphology with Arabic, but its Fidel script writes vowels, much as English does. Forty-five speakers of English, Amharic and Arabic heard CV syllable sequences of two kinds: fixed consonant with changing vowels, or fixed vowel with changing consonants. Mixed-effects models were used for the analysis. English speakers again favoured the vowel-varying sequences, and Arabic speakers again showed no difference. Amharic speakers patterned with the Arabic group rather than the English one. This points to L1 morphophonology, not orthography, as the source of the effect. It also suggests that ISR is not purely low-level phonetic memory.

Key points

  • The participants were 45 native speakers of English, Amharic and Arabic, tested in an auditory ISR task built on Kissling (2012).
  • There were two sequence types: same consonant with different vowels ("ma mi mu …") and same vowel with different consonants ("ka ma za …").
  • English speakers did better with vowel variation. Arabic and Amharic speakers performed about equally on both types.
  • On the orthography side, the Arabic abjad leaves short vowels unwritten (kataba and kutiba are spelled alike), while Amharic Fidel is an abugida that encodes vowels.
  • English speakers had higher overall accuracy, which is likely an advantage from hearing stimuli in their own language. The mixed-effects models showed no main effect of L1. Sampling confounds (students vs. staff, differing literacy exposure) are acknowledged as limitations.

Interesting ideas

  • I1. To untangle two factors that always co-occur, the study adds a third group that shares one factor with each existing group, so each explanation predicts a different outcome.
  • I2. The meaningful signal is the within-group difference between conditions, not the overall score levels, which a baseline advantage can distort.
  • I3. The CV hypothesis holds that consonants mostly carry lexical identity and vowels carry more grammatical information, which makes consonant skeletons a strong cue for word identity.
  • I4. The abjad example (kataba/kutiba spelled identically) shows a reader keeping an underspecified form and filling in the missing vowels from morphosyntactic context.
  • I5. The same units win or lose depending on the task: acoustic salience favours vowels in recall, while lexical load favours consonants in priming.

For Mova

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

  • I1 (learn): Build evaluation sets with pairs of corpora or genres that differ in only one property, so a gain can be credited to one cause rather than a mix.
  • I2 (learn): Compare parsers by their gap between construction types inside each test set, so domain-wide accuracy shifts do not hide real interaction effects.
  • I3 (tokens): Use a consonant-skeleton key as a fallback index for misspelled or unknown words, proposing lemma candidates that a tagger can then verify.
  • I4 (tree): Let ambiguous tokens carry multiple morphological readings into parsing and settle them from syntactic context, instead of committing early.
  • I5 (learn): Test every component on several task types, because a feature that looks dominant on one benchmark may matter little on another.

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

🎓Georgetown UniversityWashington · United States69 works · 4,417 citations

📚 Shelves 7The field of science this work belongs to (OpenAlex fields).Arts and Humanities · 9,296 worksLanguage and Linguistics · 9,206 worksPsychology · 798 worksExperimental and Cognitive Psychology · 463 worksDevelopmental and Educational Psychology · 260 worksNeuroscience · 95 worksCognitive Neuroscience · 95 works

🧭 Topics 1Research subjects and languages the work is about.Semitic languages · 1,484 works

Cite

Cite as Maya L. Barzilai. 2019. Templaticity Effects on Differential Processing of Consonants and Vowels. Laboratory Phonology 10.

The paper itself, not this page. BibTeX from the library's record of the work. DOI 10.5334/labphon.180

@inproceedings{barzilai2019templaticity,
  title = {{Templaticity Effects on Differential Processing of Consonants and Vowels}},
  author = {Maya L. Barzilai},
  booktitle = {Laboratory Phonology 10},
  year = {2019},
  doi = {10.5334/labphon.180},
  url = {https://doi.org/10.5334/labphon.180}
}

References

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  17. How to cite this article: Barzilai, M. L. 2019 Templaticity Effects on Differential Processing of Consonants and Vowels. Laboratory Phonology: Journal of the Association for Laboratory Phonology 10(1): 17, pp. 1–16. DOI: https://doi.org/10.5334/labphon.180 ↗
  18. Submitted: 14 November 2018 find
  19. Accepted: 23 September 2019 find
  20. Published: 17 October 2019 find
  21. Copyright: © 2019 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/. ↗

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