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Record W4400285399 · doi:10.1121/10.0027724

Generalization of inter-articulator timing control: Evidence from tongue-jaw and lip-jaw kinematics using electromagnetic articulography

2024· article· en· W4400285399 on OpenAlexaff
Matthew Masapollo, Kara Kent, Rosalie Gendron, Hannah J. Thomas, Nathan D. Maxfield, Susan Nittrouer

Bibliographic record

VenueThe Journal of the Acoustical Society of America · 2024
Typearticle
Languageen
FieldPsychology
TopicPhonetics and Phonology Research
Canadian institutionsMcGill University
Fundersnot available
KeywordsArticulatorKinematicsTongueGeneralizationOrthodonticsComputer scienceDentistryMedicineMathematicsPhysics

Abstract

fetched live from OpenAlex

Recent research in speech production indicates that talkers reliably control the relative timing of articulator movement onsets across variation in production rate, syllable stress, and segmental makeup and that this precision of inter-articulator timing control instantiates phonetic structure. To date, these timing relations have been highly reliable for tongue-jaw kinematics. In the present study, we address the generality of these timing relations to lip-jaw kinematics. Eleven talkers recorded 240 /tV#Cat/ and 240 / bV#Cab/ utterances using electromagnetic articulography, with alternative V (/ɑ/-/ɛ/) and C (/t/−/d/ or /p/−/b/), across changes in production rate (fast-normal) and stress (first syllable stressed-unstressed). To quantify inter-articulator temporal coordination, the timing of either tongue-tip or lower-lip raising onset for the intervocalic C, relative to the jaw opening-closing cycle for V, was obtained. Results indicate that the same kinematic pattern occurred among both sets of articulators: any manipulation that shortened the jaw opening-closing cycle reduced the latency of either tongue-tip or lower-lip movement onset, relative to the onset of jaw opening. Furthermore, the movement onset latencies of the tongue-tip and lower-lip were both highly differentiated by utterance type, bolstering the view that inter-articulator timing relations instantiate phonetic structure in the resulting acoustic signal.

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)0.001
metaresearch head score (Gemma)0.008
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
Metaresearch0.0010.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.033
GPT teacher head0.336
Teacher spread0.303 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

Explore more

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