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Links Between Perception and Production

2018· reference-entry· en· W2891081461 on OpenAlexaff
Carolyn McGettigan, Pascale Tremblay

Bibliographic record

Venuenot available
Typereference-entry
Languageen
FieldPsychology
TopicAction Observation and Synchronization
Canadian institutionsUniversité LavalInstitut Universitaire en Santé Mentale de Québec
Fundersnot available
KeywordsPerceptionSpeech productionPsychologyCognitive psychologyMotor theory of speech perceptionCognitive scienceSpeech perceptionField (mathematics)CognitionNeuroscienceComputer scienceSpeech recognition

Abstract

fetched live from OpenAlex

Speaking requires learning to map the relationships between oral movements and the resulting acoustical signal, which demands a close interaction between perceptual and motor systems. Though historically seen as distinct, the neural mechanisms controlling speech perception and production mechanisms are now conceptualized as largely interacting and possibly overlapping. This chapter charts the history of theoretical and empirical approaches to the interaction of perception and production, focusing on the Motor Theory of Speech Perception and its later revival within the field of cognitive neuroscience. Including insights from recent advances in neuroscience methods, as well as evidence from aging and patient populations, the chapter offers an up-to-date assessment of the question of how motor and premotor cortices contribute to speech perception.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.264
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0010.001
Insufficient payload (model declined to judge)0.0160.002

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 head0.080
GPT teacher head0.348
Teacher spread0.268 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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

Citations8
Published2018
Admission routes1
Has abstractyes

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