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Record W4386050649 · doi:10.31234/osf.io/56zwg

Language Enables the Acquisition of Distinct Sensorimotor Memories for Speech

2023· preprint· en· W4386050649 on OpenAlexafffund
Daniel R. Lametti, Emma D. Wheeler, Imane Hocine, Douglas M. Shiller

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldPsychology
TopicHearing Impairment and Communication
Canadian institutionsUniversité de MontréalAcadia University
FundersNatural Sciences and Engineering Research Council of CanadaUniversities Space Research Association
KeywordsRecallSentenceContext (archaeology)PsychologySpeech productionLinguisticsMotor theory of speech perceptionCognitive psychologySpeech perceptionComputer scienceSpeech recognitionPerceptionHistoryNeuroscience

Abstract

fetched live from OpenAlex

The role of context in the acquisition and recall of sensorimotor memories has been primarily studied in limb movements, but language use requires movement and context effects abound in the psycholinguistic literature. Here, in ecologically valid speech, we test whether English-French bilinguals can use language to acquire and recall distinct motor plans for similar speech sounds. Participants experienced real-time alterations of auditory feedback while producing English and French sentences. The alterations were equal in magnitude but opposite in direction between languages. Over three experiments (n=15 in each), we observed language-specific sensorimotor learning in speech that countered the alterations and persisted after the alterations were removed. These language-specific speech motor memories were confined to sentence production, the linguistic level at which they were learned. The effects were not observed when feedback alterations were tied to a non-linguistic cue (n=15). Linguistic context can be used to acquire and recall highly specific motor memories for speech.

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)0.000
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 score0.731
Threshold uncertainty score0.511

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 integrity0.0000.000
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 head0.073
GPT teacher head0.375
Teacher spread0.302 · 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
Published2023
Admission routes2
Has abstractyes

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