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Record W4402380752 · doi:10.1038/s41598-024-71399-y

The role of audiovisual congruence in aesthetic appreciation of contemporary music and visual art

2024· article· en· W4402380752 on OpenAlexaff
Lauren Fink, Hannah Fiehn, Melanie Wald‐Fuhrmann

Bibliographic record

VenueScientific Reports · 2024
Typearticle
Languageen
FieldPsychology
TopicMultisensory perception and integration
Canadian institutionsMcMaster University
FundersMax-Planck-Gesellschaft
KeywordsCongruence (geometry)ModalitiesAudio visualPsychologyFeelingCognitive psychologyModalAestheticsVisual artsComputer scienceArtMultimediaSocial psychology

Abstract

fetched live from OpenAlex

Does congruence between auditory and visual modalities affect aesthetic experience? While cross-modal correspondences between vision and hearing are well-documented, previous studies show conflicting results regarding whether audiovisual correspondence affects subjective aesthetic experience. Here, in collaboration with the Kentler International Drawing Space (NYC, USA), we depart from previous research by using music specifically composed to pair with visual art in the professionally-curated Music as Image and Metaphor exhibition. Our pre-registered online experiment consisted of 4 conditions: Audio, Visual, Audio-Visual-Intended (artist-intended pairing of art/music), and Audio-Visual-Random (random shuffling). Participants (N = 201) were presented with 16 pieces and could click to proceed to the next piece whenever they liked. We used time spent as an implicit index of aesthetic interest. Additionally, after each piece, participants were asked about their subjective experience (e.g., feeling moved). We found that participants spent significantly more time with Audio, followed by Audiovisual, followed by Visual pieces; however, they felt most moved in the Audiovisual (bi-modal) conditions. Ratings of audiovisual correspondence were significantly higher for the Audiovisual-Intended compared to Audiovisual-Random condition; interestingly, though, there were no significant differences between intended and random conditions on any other subjective rating scale, or for time spent. Collectively, these results call into question the relationship between cross-modal correspondence and aesthetic appreciation. Additionally, the results complicate the use of time spent as an implicit measure of aesthetic experience.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.568
Threshold uncertainty score0.326

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)0.0000.000

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 head0.027
GPT teacher head0.330
Teacher spread0.303 · 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 designNot applicable
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

Citations9
Published2024
Admission routes1
Has abstractyes

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