Time series analysis of the Kurdish long necked lute, tanbour
Bibliographic record
Abstract
There are a variety of long necked, plucked string lutes in the East with the universal name tanbour/tanbur. This research concentrates on the three-stringed fretted tanbour of Yarsan Kurds of Gouran, which is the prevailing derivative of ancient tanbour originated from Persia. Contrary to most of Western stringed instruments, the vibration in tanbour is not limited to soundboard, especially at higher frequencies. This fact, along with string tension modulation, creates a nonlinear vibration of the body and neck. Therefore, the single channel sound pickup and linear modeling is not representing tanbour’s complex sound field. Utilizing an array of four microphones, three spreading in front of soundboard and one in back of body, the system transfer function for tanbour’s main plectrum was derived via suitably optimizing a nonlinear-auto-regressive-exogenous model with the envelope of signals extracted from five tanbours with different known body sizes. Besides neck length and body width, length, and depth, the location of bridge is incorporated in the model, since it has a major role in the vibration, quality, and final setup of tanbour. Employing this model and tanbour’s physical sizes, one can estimate the optimal bridge location on the sound board to achieve finest vibration in any tanbour.
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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 | 0.001 |
| 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) | 0.001 | 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".