MétaCan
Menu
Back to cohort
Record W2058781072 · doi:10.1121/1.4786930

Time marching spectral analysis of a swept sine melody model

2006· article· en· W2058781072 on OpenAlexaff
Rama Bhat

Bibliographic record

VenueThe Journal of the Acoustical Society of America · 2006
Typearticle
Languageen
FieldComputer Science
TopicMusic Technology and Sound Studies
Canadian institutionsConcordia University
Fundersnot available
KeywordsHarmonicsMelodyRendering (computer graphics)Octave (electronics)Computer scienceVibratoAcousticsSine waveFundamental frequencyMathematicsSpeech recognitionMusicalArtificial intelligencePhysicsArt

Abstract

fetched live from OpenAlex

A melody is a progression of musical notes in a scale. Since the notes have identified frequencies, a melody rendering involves a quick sweep of frequencies between any two neighboring notes, and a dwell at the notes. A melody rendering is modeled as a dwell at the notes and a sinusoidal sweep in between. A time marching spectral analysis shows that the dwell time and the rate of sweep between notes have significant influence on the melody. Any two notes form the not-so-high harmonics of a periodic process which may or may not necessarily contain the fundamental and some of the lower harmonics. If a three-note combination of a first, a fifth, and an octave higher notes are taken, as the drone in Indian classical music, they have ratios of 1:3/2:2. The combination is a periodic process with half of the first note frequency as the fundamental which is missing, while the second, third, and fourth harmonics are present. A melodic rendering of seven notes or less may be construed as a periodic process with some of the harmonics varying or dancing with time. Results on a melody in pentatonic scale is presented and discussed.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.007
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.008
GPT teacher head0.231
Teacher spread0.223 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations0
Published2006
Admission routes1
Has abstractyes

Explore more

Same venueThe Journal of the Acoustical Society of AmericaSame topicMusic Technology and Sound StudiesFrench-language works237,207