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Record W3160668727 · doi:10.18280/ts.380218

Investigation of Timbral Qualities of Guitar Using Wavelet Analysis

2021· article· en· W3160668727 on OpenAlexvenueno aff
Şafak Ekmen, Can Karadoğan

Bibliographic record

VenueTraitement du signal · 2021
Typearticle
Languageen
FieldComputer Science
TopicMusic and Audio Processing
Canadian institutionsnot available
Fundersnot available
KeywordsGuitarWaveletSpeech recognitionComputer scienceArtificial intelligenceAcousticsPhysics

Abstract

fetched live from OpenAlex

Aim of this study is presenting a practical and accurate approach for objective evaluation of guitars that is suitable for performing by the different parties of the field. For this purpose, timbral qualities of classical guitars are investigated using the power of wavelet analysis. A complete system from data capturing to their analysis is proposed. A mass produced guitar that is described as a learning guitar by its production company and a luthier-made guitar are analyzed. Procedure is done with the piezo-film sensors attached to the guitar and the player holding it in a conventional playing position while plucking the strings with a pluck. Continuous Wavelet and Wavelet Packet Transforms are employed for analysis using MATLAB Wavelet Toolbox. High resolution results show detailed presentation of harmonic and inharmonic partials as well as time envelopes of them. This allows for objective analysis on the timbre of a guitar as well as making comparison between the timbral properties of two guitars.

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.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.370
Threshold uncertainty score0.299

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.058
GPT teacher head0.264
Teacher spread0.206 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2021
Admission routes1
Has abstractyes

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