The effects of timbre on harmonic interval tuning and perception
Bibliographic record
Abstract
In Western music, temperament grants ease of performance and listening especially when it comes to harmony, whose multiplicity is built upon instrument intonation. However, our fluid perception allows other aspects of music such as timbre, blend and sensory dissonance to affect intonation. This thesis investigates how musicians perceive and compensate for the interacting effects of timbre, blend and sensory dissonance when tuning and rating harmonic intervals. The first two experiments involved an interval-tuning task and the third experiment involved a perceptual rating task for the unison, minor second, major third, tritone, perfect fifth, major sixth, minor seventh and octave. A different sample of twenty musically trained subjects participated in each experiment. In Experiment 1, participants tuned the upper note of an isolated harmonic dyad. Six timbre pairs comprised of the harpsichord, piano, clarinet and flute were chosen to reflect low to high blend. In Experiment 2, participants tuned the lower and upper note of an isolated harmonic dyad. Stimuli consisted of twelve pairs based on combinations of the harpsichord, trumpet, vibraphone and flute, chosen based on brightness and playing mechanism. In Experiment 3, participants rated all of the stimuli from Experiments 1 and 2 on three continuous scales representing subjective measures of auditory roughness, blend and pleasantness. Overall results showed lower tuning accuracy from equal temperament for musically consonant intervals regardless of pair, but higher tuning variability for musically dissonant intervals. Findings in relation to pairs with the flute and harpsichord supported previous research on increased distance in a timbre space suggesting decreased blend (Kendall and Carterette, 1993). Significant order differences in tuning were found mostly in relation to the pairs with the harpsichord as one of its instruments at consonant intervals. Musicians favoured interval contraction when tuning harpsichord pairs if the harpsichord was playing the upper note and interval expansion if it was playing the lower note, regardless of the instrument playing the note that was being tuned. Findings from Experiment 3 suggest that instrument assignment to upper and lower notes does not affect perceptual judgments of the overall timbre of a harmonic interval, but does affect the tuning of such intervals. Roughness and pleasantness ratings depended on the inclusion of the trumpet (rough, unpleasant) or vibraphone (smooth, pleasant), whereas blend ratings depended on whether or not instrument pairs had similar or different playing mechanisms. These perceptual ratings were not correlated with the tuning deviations found in Experiments 1 and 2. Further research with a wider variation in timbre combinations will need to be conducted to explore whether or not these tuning differences are particular to the harpsichord due to its overall timbre, or due to a combination of its timbral properties that can be generalized to other instruments.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".