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Record W2072253497 · doi:10.1121/1.4785854

Sensitivity to intermodal asynchrony between acoustic and structural vibrations

2005· article· en· W2072253497 on OpenAlexaffabout
Kent Walker, William L. Martens

Bibliographic record

VenueThe Journal of the Acoustical Society of America · 2005
Typearticle
Languageen
FieldHealth Professions
TopicNoise Effects and Management
Canadian institutionsMcGill University
Fundersnot available
KeywordsAcousticsAsynchrony (computer programming)LoudspeakerPsychoacousticsPsychometric functionModalComputer scienceSensitivity (control systems)VibrationPerceptionPsychologyPsychophysicsPhysicsTelecommunications

Abstract

fetched live from OpenAlex

The purpose of this study was to discover the attributes of musical stimuli which facilitate sensory integration in bi-modal music reproduction systems incorporating sound and whole-body vibration. It was hypothesized that subjective judgments regarding bimodal synchrony would vary depending on the spectral, temporal, and spatial properties of the stimuli. To test this hypothesis, musical instruments with significant low frequency energy and a variety of spectra-temporal envelopes were recorded. These stimuli were then reproduced with varying intermodal delay and overlap in frequency content between displayed vibratory and acoustic components. The air-born component of the bimodal stimuli was presented via a multichannel loudspeaker array, with a direct sound component, as well as a reproduced indirect sound arriving from all around the observer. Psychometric functions were constructed for time order judgment (TOJ) over a range of intermodal delay values. Changes in the slope and intercept of the transformed psychometric functions gave a clear picture of the influence of spectra-temporal and spatial parameters of the multimodal stimuli, the most striking results being the decreased tolerance for intermodal asynchrony associated with instruments recorded in reverberant environments. [Work supported by a Grant from VRQ of the Government of Quebec.]

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.526
Threshold uncertainty score0.428

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 studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.019
GPT teacher head0.346
Teacher spread0.327 · 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.

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

Citations1
Published2005
Admission routes2
Has abstractyes

Explore more

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