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Record W4252832767 · doi:10.1121/1.4800579

Producing whole speech events: Anticipatory lip compression in bilabial stops

2013· article· en· W4252832767 on OpenAlexaff
Chenhao Chiu, Bryan Gick

Bibliographic record

VenueProceedings of meetings on acoustics · 2013
Typearticle
Languageen
FieldPsychology
TopicPhonetics and Phonology Research
Canadian institutionsUniversity of British Columbia HospitalUniversity of British Columbia
Fundersnot available
KeywordsSpeech productionKinematicsTRACE (psycholinguistics)Speech recognitionCompression (physics)AerodynamicsPsychologyComputer scienceEngineeringLinguisticsPhysics

Abstract

fetched live from OpenAlex

Bilabial stops /b/, /p/, and /m/ ostensibly share a common lip constriction. Recent evidence shows that different bilabial stops involve distinct facial muscle activations, suggesting that oral speech movements anticipate aerodynamic conditions [Gick et al. 2pSC1 Proc. Acoust. 2012 H.K.]. The present study investigates how the lips themselves behave in whole speech events. Existing models of speech production governing only articulatory motions predict that lip compression would respond to changes in aerodynamic conditions rather than anticipating such changes; a model that includes whole events predicts anticipatory activation of lip muscles with concomitant kinematic lip compression, but only in cases where a real increase in air pressure is expected. Lip kinematics were recorded using OptoTrak to trace lip movements of bilabial stops in response to imperative acoustic stimuli. Results show consistent anticipatory lip compression in spoken /b/, but not in non-speech jaw opening movements and only sporadic compression in mouthed /b/, where air pressure is not expected to increase. Biomechanical simulation using an orofacial model developed within the Artisynth simulation toolkit (www.artisynth.org) confirms anticipatory muscle activations. These findings support a model of speech tasks wherein coordinated body-level muscular systems govern whole speech events.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.830
Threshold uncertainty score0.903

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 science0.0010.000
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 head0.030
GPT teacher head0.322
Teacher spread0.292 · 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

Citations1
Published2013
Admission routes1
Has abstractyes

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