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Record W1990126510 · doi:10.1044/jslhr.4301.158

Effects of Facial Paralysis and Audiovisual Information on Stop Place Identification

2000· article· en· W1990126510 on OpenAlexafffund
Monica A. Nelson, Megan Hodge

Bibliographic record

VenueJournal of Speech Language and Hearing Research · 2000
Typearticle
Languageen
FieldPsychology
TopicMultisensory perception and integration
Canadian institutionsUniversity of Alberta
FundersGlenrose Rehabilitation Hospital
KeywordsPsychologyPerceptionAudiologyVoice-onset timeMode (computer interface)Place of articulationPresentation (obstetrics)Speech recognitionConsonantVowelComputer scienceMedicine

Abstract

fetched live from OpenAlex

This study investigated how listeners' perceptions of bilabial and lingua-alveolar voiced stops in auditory (A) and audiovisual (AV) presentation modes were influenced by articulatory function in a girl with bilateral facial paralysis (BFP) and a girl with normal facial movement (NFM). The Fuzzy Logic Model of Perception (FLMP) was used to make predictions about listeners' identifications of stop place based on assumptions about the nature (clear, ambiguous, or conflicting) of the A or AV cues produced by each child during /b/ and /d/ CV syllables. As predicted, (a) listeners' identification scores for NFM were very high and reliable, regardless of presentation mode or stop place, (b) listeners' identification scores for BFP were high for lingua-alveolar place, regardless of presentation mode, but more variable and less reliable than for NFM; significantly lower (overall at a chance level) for bilabial place in the A mode; and lowest for bilabial place in the AV mode. Conflicting visual cues for stop place for BFP's productions of /bV/ syllables influenced listeners' perceptions, resulting in most of her bilabial syllables being misidentified in the AV mode. F2 locus equations for each child's /bV/ and /dV/ syllables showed patterns similar to those reported by previous investigators, but with less differentiation between stop place for BFP than NFM. These acoustic results corresponded to the perceptual results obtained. (That is, when presented with only auditory information, on average, listeners perceived BFP's target /b/ syllables to be near the boundary between /b/ and /d/.)

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.943
Threshold uncertainty score1.000

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)0.0010.000

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 head0.050
GPT teacher head0.429
Teacher spread0.379 · 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 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

Citations13
Published2000
Admission routes2
Has abstractyes

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