Evidence map›Paper›PMID 37553536›Full record

ArticleBehavior research methods2024

Orthography-phonology consistency in English: Theory- and data-driven measures and their impact on auditory vs. visual word recognition.

Alfred Lim, Beth O'Brien, Luca Onnis

Abstract read
In one paragraph

Article in Behavior research methods, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Alfred LimSchool of Psychology, University of Nottingham Malaysia, Semenyih, Selangor, Malaysia.ORCID 0000-0002-9818-8130
Beth O'BrienCentre for Research in Child Development (CRCD), National Institute of Education, Singapore, Singapore.
Luca OnnisCentre for Multilingualism in Society across the Lifespan, University of Oslo, Semenyih, Selangor, Malaysia. luca.onnis@iln.uio.no.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Research on orthographic consistency in English words has selectively identified different sub-syllabic units in isolation (grapheme, onset, vowel, coda, rime), yet there is no comprehensive assessment of how these measures affect word identification when taken together. To study which aspects of consistency are more psychologically relevant, we investigated their independent and composite effects on human reading behavior using large-scale databases. Study 1 found effects on adults' naming responses of both feedforward consistency (orthography to phonology) and feedback consistency (phonology to orthography). Study 2 found feedback but no feedforward consistency effects on visual and auditory lexical decision tasks, with the best predictor being a composite measure of consistency across grapheme, rime, OVC, and word-initial letter-phoneme. In Study 3, we explicitly modeled the reading process with forward and backward flow in a bidirectionally connected neural network. The model captured latent dimensions of quasi-regular mapping that explain additional variance in human reading and spelling behavior, compared to the established measures. Together, the results suggest interactive activation between phonological and orthographic word representations. They also validate the role of computational analyses of language to better understand how print maps to sound, and what properties of natural language affect reading complexity.

Indexed as

PhoneticsSpeech PerceptionAdultData ManagementHumansLanguageReadingComputational modellingLexical decisionSound-spelling consistencySpelling-sound consistencyWord namingWord recognition

Identifiers

PMID37553536
PMCPMC10991026

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LicenceCC BY
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.