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The Speech Focus Position Effect on Jaw–Finger Coordination in a Pointing Task

2008· article· en· W2116748651 on OpenAlexaboutno aff
Amélie Rochet‐Capellan, Rafael Laboissière, Jean‐Luc Schwartz

Bibliographic record

VenueJournal of Speech Language and Hearing Research · 2008
Typearticle
Languageen
FieldPsychology
TopicHearing Impairment and Communication
Canadian institutionsnot available
Fundersnot available
KeywordsGestureSyllableStress (linguistics)Speech recognitionFocus (optics)Word (group theory)Offset (computer science)CommunicationComputer sciencePsychologyArtificial intelligenceMathematicsLinguisticsPhysicsGeometry

Abstract

fetched live from OpenAlex

PURPOSE: This article investigates jaw-finger coordination in a task involving pointing to a target while naming it with a CVCV (e.g., /papa/) versus CVCV (e.g., /papa/) word. According to the authors' working hypothesis, the pointing apex (gesture extremum) would be synchronized with the apex of the jaw-opening gesture corresponding to the stressed syllable. METHOD: Jaw and finger motions were recorded using Optotrak (Northern Digital, Waterloo, Ontario, Canada). The effects of stress position on jaw-finger coordination were tested across different target positions (near vs. far) and different consonants in the target word (/t/ vs. /p/). Twenty native Portuguese Brazilian speakers participated in the experiment (all conditions). RESULTS: Jaw response starts earlier, and finger-target alignment period is longer for CVCV words than for CVCV ones. The apex of the jaw-opening gesture for the stressed syllable appears synchronized with the onset of the finger-target alignment period (corresponding to the pointing apex) for CVCV words and with the offset of that period for CVCV words. CONCLUSIONS: For both stress conditions, the stressed syllable occurs within the finger-target alignment period because of tight finger-jaw coordination. This result is interpreted as evidence for an anchoring of the speech deictic site (part of speech that shows) in the pointing gesture.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.866
Threshold uncertainty score0.462

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.058
GPT teacher head0.409
Teacher spread0.351 · 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 teacher head, 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

Citations70
Published2008
Admission routes1
Has abstractyes

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