Vowel content influences relative pitch perception in vocal melodies: A comparison of models based on brightness vs. intrinsic pitch of vowels
Bibliographic record
Abstract
Past research involving real and synthesized instrumental timbres has found that note-to-note changes in brightness can influence perception of interval size. Changes that are congruent with changes in pitch led to an expansion, whereas changes that are incongruent lead to a contraction. In the case of singing, the brightness of individual notes (as measured by the spectral centroid) will vary as a function of vowel content. In a recent study, we investigated whether note-to-note changes in the brightness of sung notes were capable of influencing the perception of interval size. While results were consistent with past work on instrumental timbres, we were not able to completely rule out an alternative explanation concerning a perceptual correction for the intrinsic pitch of vowels (e.g., f0 of /i/ tends to be produced higher than /a/). In the present study, we created 288 unique note pairs that varied with regard to absolute change in f0 as well as vowel content. Vowels were sampled from across the vowel space, which allowed us to generate unique predictors for change in brightness (spectral centroid) and changes in intrinsic pitch (F2). Regression analyses will compare the effectiveness of competing models.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".