Evidence map›Paper›PMID 42056261›Full record

ArticleBehavior research methods2026

Word frequency and contextual diversity measures for Singapore English.

Zehua R Jiang, Cynthia S Q Siew

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In one paragraph

Article in Behavior research methods, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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4 · The record

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5 · Who and what money

Authors and funding

2 authors.

Zehua R JiangDepartment of Psychology, National University of Singapore, 9 Arts Link, Block AS4, Singapore, 117570, Singapore.ORCID http://orcid.org/0009-0005-2868-324X
Cynthia S Q SiewDepartment of Psychology, National University of Singapore, 9 Arts Link, Block AS4, Singapore, 117570, Singapore. cynthia@nus.edu.sg.ORCID http://orcid.org/0000-0003-3384-7374

Funding

China Scholarship Council 202306320298Social Science Research Council of Singapore MOE 2021-SSHR-003
6 · The paper itself

Abstract

Singapore English, shaped by unique historical and sociocultural factors, diverges significantly from American and British English varieties. Despite its centrality in Singapore's communication landscape, comprehensive word frequency estimates for this dialect have been lacking, limiting psycholinguistic research that accurately reflects local language processing. Dialectal variation fundamentally influences cognitive mechanisms, and neglecting these differences can distort theoretical models of language processing. This study addresses this gap by constructing word frequency (WF) and contextual diversity (CD) estimates from the National Speech Corpus (NSC), a large-scale speech corpus of Singapore English. We analyzed three NSC subparts comprising over 10,000 transcripts and 30 + million words to generate frequency estimates for 50,000 words, including both standard and uniquely Singaporean terms. To validate these measures, we used lexical decision data from the Auditory English Lexicon Project, featuring Singaporean participants who responded to stimuli across different accent conditions. Linear and binomial mixed-effect models compared NSC-based estimates against SUBTLEX-US and SUBTLEX-UK in predicting reaction times and accuracy. NSC estimates produced the lowest Akaike information criterion (AIC) values across both British and Singaporean accents, indicating superior fit to local language processing patterns. These results demonstrate that WF and CD effects are shaped by specific language experiences and highlight the necessity of dialect-appropriate psycholinguistic tools. This database advances cognitive science by enabling more accurate modeling of dialect-sensitive language processing, representing one of the largest psycholinguistic resources available for a less-studied English variety, and underscores the importance of developing similar resources for other English varieties worldwide.

Indexed as

LanguagePsycholinguisticsHumansSingaporeSpeechContextual diversityEnglish dialectsSingapore EnglishWord frequency

Identifiers

PMID42056261
PMCPMC13128781

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