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Record W2592320872 · doi:10.1044/2016_jslhr-s-16-0019

The Quantal Larynx: The Stable Regions of Laryngeal Biomechanics and Implications for Speech Production

2017· article· en· W2592320872 on OpenAlexafffund
Scott R. Moisik, Bryan Gick

Bibliographic record

VenueJournal of Speech Language and Hearing Research · 2017
Typearticle
Languageen
FieldMedicine
TopicVoice and Speech Disorders
Canadian institutionsUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsLarynxSpeech productionPhonationBiomechanicsVocal foldsAudiologyGlottisPsychologyCommunicationMedicineSpeech recognitionAnatomyComputer science

Abstract

fetched live from OpenAlex

Purpose: Recent proposals suggest that (a) the high dimensionality of speech motor control may be reduced via modular neuromuscular organization that takes advantage of intrinsic biomechanical regions of stability and (b) computational modeling provides a means to study whether and how such modularization works. In this study, the focus is on the larynx, a structure that is fundamental to speech production because of its role in phonation and numerous articulatory functions. Method: A 3-dimensional model of the larynx was created using the ArtiSynth platform (http://www.artisynth.org). This model was used to simulate laryngeal articulatory states, including inspiration, glottal fricative, modal prephonation, plain glottal stop, vocal-ventricular stop, and aryepiglotto-epiglottal stop and fricative. Results: Speech-relevant laryngeal biomechanics is rich with "quantal" or highly stable regions within muscle activation space. Conclusions: Quantal laryngeal biomechanics complement a modular view of speech control and have implications for the articulatory-biomechanical grounding of numerous phonetic and phonological phenomena.

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)0.003
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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.476
Threshold uncertainty score0.893

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.120
GPT teacher head0.435
Teacher spread0.315 · 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 designBench or experimental
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

Citations33
Published2017
Admission routes2
Has abstractyes

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