Exploring the perception of violin qualities: student- vs. performance-level instruments, strings and soundpost height
Bibliographic record
Abstract
The violin has reached its current, highly refined form over centuries through empirical methods, with some of the most valuable instruments being made more than 300 years ago.It is thus perhaps remarkable that very little is understood about violin quality and what particular aspects of the instrument are most important in the perception of violin qualities.This thesis reports three perceptual experiments that were designed to help better understand the relationship between a violin's perceived qualities and its physical structure.Previous studies [Saitis et al., 2012; Fritz et al., 2012bFritz et al., , 2014] ] have shown a general lack of agreement among players in terms of violin preference when evaluating instruments intended for intermediate to advanced players ($1300 CAD and higher).The first experiment of this thesis explored whether there would be greater perceptual agreement when comparing violins meant for entry-level vs. advanced players, whether there would be significant perceptual differences between these two categories of violins and whether some structural vibration characteristics could be found to explain these differences.The results showed that performance violins were on average rated significantly higher than student violins in terms of preference and the three attribute criteria clarity, richness and balance.The second and third studies of this thesis investigated the origin of the disagreement among players through two specific modifications to the violin.The second study investigated how different strings affect the perception of violin qualities.Two violins of the same make with similar sound quality and playability were employed.They were both strung with Dominant strings initially.Subjects played the violins, described and rated the difference (on eight criteriaresponsiveness, power, resonance, brightness, clarity, richness, balance and overall quality) between the two violins during a session labeled D1-D2.Subsequently, the strings of violin 2 were changed to a different brand (Kaplan or Pro-Art), unbeknownst to the players, and players had to re-evaluate the differences between the two violins (session D1-K2 or D1-P2).Results showed no significant differences between the experimental conditions except that the brightness difference ratings obtained in D1-D2 were found to be significantly higher than those in D1-P2.The third study involved both playing and listening (using recorded sounds) experiments to investigate how changes in soundpost height (for a fixed soundpost position) affect the perceptual qualities of the violin and what is the threshold of change below which players and
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.002 | 0.001 |
| 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".