Why this work is in the frame
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Bibliographic record
Abstract
This dissertation proposes an interdisciplinary approach for the study of the timbre of the classical guitar. We start by identifying the static; control parameters of timbre, relating to the structural components of the guitar and the dynamic control parameters of timbre, relating to the gestures applied by the performer on the instrument. From the plucked string physical model (obtained from the transverse wave equation), we derive a digital signal interpretation of the plucking effect which is a comb filtering. Then we investigate how subjective characteristics of sound, like timbre, are related to gesture parameters. The starting point for exploration is an inventory of verbal descriptors commonly used by professional musicians to describe the brightness, the colour, the shape and the texture of the sounds they produce on their instruments. An explanation for the voice-like nature of guitar tones is proposed based on the observation that the maxima of the comb-filter-shaped magnitude spectrum of guitar tones are located at frequencies similar to the formant frequencies of a subset of identifiable vowels. These analogies at the spectral level might account for the origin of some timbre descriptors such as open, oval, round, thin, closed, nasal and hollow, that seem to refer to phonetic gestures. In a experiment conducted to confirm these analogies, participants were asked to associate a consonant to the attack and a vowel to the decay of guitar tones. The results of this study support the idea that some perceptual dimensions of the guitar timbre space can be borrowed from phonetics. Finally, we address the problem of the indirect acquisition of instrumental gesture parameters. Pursuing previous research on the estimation of the plucking position from a recording, we propose a new estimation method based on an iterative weighted least-square algorithm, starting from a first approximation derived from a variant of the autocorrelation func
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.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.003 | 0.004 |
| 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 it