MétaCan
Menu
Back to cohort
Record W4246945909 · doi:10.1121/1.4799848

Auditory plasticity and sensorimotor learning in speech production

2013· article· en· W4246945909 on OpenAlexafffund
Douglas M. Shiller, Daniel R. Lametti, David J. Ostry

Bibliographic record

VenueProceedings of meetings on acoustics · 2013
Typearticle
Languageen
FieldPsychology
TopicLanguage Development and Disorders
Canadian institutionsMcGill UniversityUniversité de Montréal
FundersNational Institute on Deafness and Other Communication DisordersFonds de recherche du Québec – Nature et technologiesFonds Québécois de la Recherche sur la Nature et les Technologies
KeywordsNeurocomputational speech processingSpeech productionAuditory feedbackSensory systemMotor theory of speech perceptionPerceptionMotor controlAdaptation (eye)Computer scienceSpeech perceptionPsychologySpeech recognitionCognitive psychologyNeuroscience

Abstract

fetched live from OpenAlex

Numerous studies have shown the speech motor system to be highly flexible and responsive to changes in sensory input, revealing a central role for both auditory and somatosensory feedback in the acquisition and maintenance of speech motor control. Consistent with these studies, models of speech production have highlighted the role of accurate, stable sensory representations that serve, in part, as the goals of speech movements. A separate body of work has demonstrated that auditory-sensory representations of speech sounds are not perfectly stable, but rather exhibit rapid adaptation to changing input conditions in children and adults. The plasticity of auditory representations has important implications for the control of speech production, both in early speech motor development and in the sensory-based maintenance of speech accuracy that characterizes adult speech motor control. Here, we describe two studies that explore the link between sensory and motor plasticity in the speech motor system. The studies combine the paradigm of sensorimotor adaptation (altering auditory feedback during speech production) with measures and manipulations of auditory-perceptual representations of speech sounds. The results show not only that auditory speech targets can be rapidly altered, but that changes in sensory representations can have a direct impact on speech motor learning.

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)0.000
metaresearch head score (Gemma)0.002
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 score0.549
Threshold uncertainty score0.579

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
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 integrity0.0000.000
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 head0.008
GPT teacher head0.240
Teacher spread0.231 · 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 routes2
Has abstractyes

Explore more

Same venueProceedings of meetings on acousticsSame topicLanguage Development and DisordersFrench-language works237,207