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Record W1973756445 · doi:10.1121/1.3531932

Probing the independence of formant control using altered auditory feedback

2011· review· en· W1973756445 on OpenAlexafffund
Ewen MacDonald, David W. Purcell, Kevin G. Munhall

Bibliographic record

VenueThe Journal of the Acoustical Society of America · 2011
Typereview
Languageen
FieldPsychology
TopicPhonetics and Phonology Research
Canadian institutionsWestern UniversityQueen's University
FundersNational Institute on Deafness and Other Communication DisordersNatural Sciences and Engineering Research Council of Canada
KeywordsFormantAuditory feedbackVowelCorrelationAudiologySpeech productionMathematicsPopulationPsychologyAcousticsSpeech recognitionComputer sciencePhysicsMedicine

Abstract

fetched live from OpenAlex

Two auditory feedback perturbation experiments were conducted to examine the nature of control of the first two formants in vowels. In the first experiment, talkers heard their auditory feedback with either F1 or F2 shifted in frequency. Talkers altered production of the perturbed formant by changing its frequency in the opposite direction to the perturbation but did not produce a correlated alteration of the unperturbed formant. Thus, the motor control system is capable of fine-grained independent control of F1 and F2. In the second experiment, a large meta-analysis was conducted on data from talkers who received feedback where both F1 and F2 had been perturbed. A moderate correlation was found between individual compensations in F1 and F2 suggesting that the control of F1 and F2 is processed in a common manner at some level. While a wide range of individual compensation magnitudes were observed, no significant correlations were found between individuals' compensations and vowel space differences. Similarly, no significant correlations were found between individuals' compensations and variability in normal vowel production. Further, when receiving normal auditory feedback, most of the population exhibited no significant correlation between the natural variation in production of F1 and F2.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesResearch integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.882
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0020.000
Research integrity0.0000.002
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 head0.081
GPT teacher head0.372
Teacher spread0.291 · 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.

Study designNot applicable
Domainnot available
GenreReview

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

Citations63
Published2011
Admission routes2
Has abstractyes

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