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Record W2244745552 · doi:10.1159/000434719

Effects of Congenital Visual Deprivation on the Auditory Perception of Anticipatory Labial Coarticulation

2015· article· en· W2244745552 on OpenAlexaff
Lucie Ménard, Marie-Agnès Cathiard, Émilie Troille, Marilyn Giroux

Bibliographic record

VenueFolia Phoniatrica et Logopaedica · 2015
Typearticle
Languageen
FieldMedicine
TopicVoice and Speech Disorders
Canadian institutionsUniversité du Québec à MontréalCentre for Research on Brain Language and Music
Fundersnot available
KeywordsAudiologyPsychologyVowelCoarticulationPerceptionAuditory perceptionSpeech perceptionSpeech recognitionMedicineNeuroscience

Abstract

fetched live from OpenAlex

OBJECTIVE: It has been shown previously that congenitally blind francophone adults had higher auditory discrimination scores than sighted adults. It is unclear, however, if, compared to their sighted peers, blind speakers display an increased ability to detect anticipatory acoustic cues. In this paper, this ability is investigated in both speaker groups. METHODS: Using the gating paradigm, /izi/ and /izy/ sequences were truncated to include a variable duration of the vowel. The sequences were used as stimuli in an auditory identification test. Seventeen congenitally blind adults (9 females and 8 males) and 17 sighted controls were recruited. Their task was to identify the second vowel of the sequence. RESULTS: Results show that all participants could reliably identify the rounded vowel prior to its acoustic onset, but steeper identification slopes were found for sighted listeners than for blind listeners. CONCLUSION: The difference in identification slopes likely suggests that sighted speakers display finer abilities to perceptually follow the decreasing values of the frication noise, compared to blind speakers.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.021
GPT teacher head0.297
Teacher spread0.276 · 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 source (direct Gemma or distilled Codex), 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

Citations6
Published2015
Admission routes1
Has abstractyes

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