Audiovisual Interval Size Estimation Is Associated with Early Musical Training
Bibliographic record
Abstract
Although pitch is a fundamental attribute of auditory perception, substantial individual differences exist in our ability to perceive differences in pitch. Little is known about how these individual differences in the auditory modality might affect crossmodal processes such as audiovisual perception. In this study, we asked whether individual differences in pitch perception might affect audiovisual perception, as it relates to age of onset and number of years of musical training. Fifty-seven subjects made subjective ratings of interval size when given point-light displays of audio, visual, and audiovisual stimuli of sung intervals. Audiovisual stimuli were divided into congruent and incongruent (audiovisual-mismatched) stimuli. Participants' ratings correlated strongly with interval size in audio-only, visual-only, and audiovisual-congruent conditions. In the audiovisual-incongruent condition, ratings correlated more with audio than with visual stimuli, particularly for subjects who had better pitch perception abilities and higher nonverbal IQ scores. To further investigate the effects of age of onset and length of musical training, subjects were divided into musically trained and untrained groups. Results showed that among subjects with musical training, the degree to which participants' ratings correlated with auditory interval size during incongruent audiovisual perception was correlated with both nonverbal IQ and age of onset of musical training. After partialing out nonverbal IQ, pitch discrimination thresholds were no longer associated with incongruent audio scores, whereas age of onset of musical training remained associated with incongruent audio scores. These findings invite future research on the developmental effects of musical training, particularly those relating to the process of audiovisual perception.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".