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Record W4221049031 · doi:10.1017/s0025100321000335

Lateral tongue bracing as a universal postural basis for speech

2022· article· en· W4221049031 on OpenAlexafffund
Yadong Liu, Felicia Tong, Gillian de Boer, Bryan Gick

Bibliographic record

VenueJournal of the International Phonetic Association · 2022
Typearticle
Languageen
FieldPsychology
TopicPhonetics and Phonology Research
Canadian institutionsUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of CanadaNational Institutes of Health
KeywordsTongueMandarin ChineseCoronal planeBracingPsychologyLinguisticsMedicineMathematicsAnatomyGeometry

Abstract

fetched live from OpenAlex

Lateral bracing refers to an intentional tongue posture whereby the sides of the tongue make contact with the sides of the palate and the upper molars. While previous research on this topic has focused mostly on English, the present study tests the hypothesis that lateral bracing provides a fundamental postural basis for speech and is present across languages. We predicted that, across multiple languages, the sides of the tongue should be more stable than the center and should stay in a relatively high position in the mouth throughout most of running speech. Using coronal ultrasound imaging, we measured tongue movement produced by speakers (N = 28) of six languages (Akan, Cantonese, English, Korean, Mandarin and Spanish). Across these languages, as predicted, the sides of the tongue throughout running speech were positioned higher in the mouth than the center, and the range of movement of the sides was significantly smaller than that of the center of the tongue. These findings support the view that the sides of the tongue maintain a braced posture across languages while speaking, potentially constituting a universal, rather than language-specific, postural basis for speech.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.017
GPT teacher head0.320
Teacher spread0.304 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations4
Published2022
Admission routes2
Has abstractyes

Explore more

Same venueJournal of the International Phonetic AssociationSame topicPhonetics and Phonology ResearchFrench-language works237,207