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Record W2517927733 · doi:10.1044/2016_jslhr-s-15-0092

Spatial Frequency Requirements and Gaze Strategy in Visual-Only and Audiovisual Speech Perception

2016· article· en· W2517927733 on OpenAlexafffund
Amanda Wilson, Agnès Alsius, Martin Paré, Kevin G. Munhall

Bibliographic record

VenueJournal of Speech Language and Hearing Research · 2016
Typearticle
Languageen
FieldPsychology
TopicMultisensory perception and integration
Canadian institutionsQueen's University
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health Research
KeywordsSpeechreadingGazePerceptionPsychologyAudiologyVisual perceptionEye trackingSensory cueCognitive psychologyComputer scienceSpeech recognitionComputer visionMedicine

Abstract

fetched live from OpenAlex

PURPOSE: The aim of this article is to examine the effects of visual image degradation on performance and gaze behavior in audiovisual and visual-only speech perception tasks. METHOD: We presented vowel-consonant-vowel utterances visually filtered at a range of frequencies in visual-only, audiovisual congruent, and audiovisual incongruent conditions (Experiment 1; N = 66). In Experiment 2 (N = 20), participants performed a visual-only speech perception task and in Experiment 3 (N = 20) an audiovisual task while having their gaze behavior monitored using eye-tracking equipment. RESULTS: In the visual-only condition, increasing image resolution led to monotonic increases in performance, and proficient speechreaders were more affected by the removal of high spatial information than were poor speechreaders. The McGurk effect also increased with increasing visual resolution, although it was less affected by the removal of high-frequency information. Observers tended to fixate on the mouth more in visual-only perception, but gaze toward the mouth did not correlate with accuracy of silent speechreading or the magnitude of the McGurk effect. CONCLUSIONS: The results suggest that individual differences in silent speechreading and the McGurk effect are not related. This conclusion is supported by differential influences of high-resolution visual information on the 2 tasks and differences in the pattern of gaze.

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 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 score0.892
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.124
GPT teacher head0.470
Teacher spread0.346 · 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

Citations22
Published2016
Admission routes2
Has abstractyes

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