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Record W2035731087 · doi:10.1121/1.4920031

The effect of amplitude envelope on spatial ventriloquism

2015· article· en· W2035731087 on OpenAlexaff
Dominique Beauregard Cazabon, Michael Schutz

Bibliographic record

VenueThe Journal of the Acoustical Society of America · 2015
Typearticle
Languageen
FieldPsychology
TopicMultisensory perception and integration
Canadian institutionsMcMaster University
Fundersnot available
KeywordsStimulus (psychology)PerceptionComputer scienceAmplitudeSpatial frequencySpatial analysisVisual perceptionAcousticsPsychologyCognitive psychologyMathematicsPhysicsOpticsNeuroscience

Abstract

fetched live from OpenAlex

Spatial ventriloquism occurs when a visual event and an auditory event happen simultaneously; location judgments for the sound source become biased toward the location of the visual event. Evidence suggests the brain attributes greater weight to spatial information provided by the visual stimulus because the visual system offers better spatial acuity; when the visual stimulus is deteriorated, the visual bias is reduced. Thus, the brain performs optimal bimodal integration: greater weight is given to the modality which provides more information. The present study aims to determine whether the amplitude envelope of sounds provides spatial localization information to the perceptual system. We used a psychophysical staircase procedure to measure spatial ventriloquism experienced by participants for sounds with percussive, flat, and time-reversed percussive envelopes. We hypothesize that percussive and reverse-percussive sounds provide more information and thus better sound localization acuity than flat sounds, which would result in smaller degrees of spatial ventriloquism for the former than the latter. The results yield insight into the brain’s use of auditory cues in audio-visual integration.

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)0.001
metaresearch head score (Gemma)0.012
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
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 head0.031
GPT teacher head0.337
Teacher spread0.306 · 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 designBench or experimental
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

Citations0
Published2015
Admission routes1
Has abstractyes

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