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Record W2560646025 · doi:10.1121/1.4971204

Perceptually salient spectrotemporal modulations for recognition of sustained musical instruments

2016· article· en· W2560646025 on OpenAlex
Etienne Thoret, Philippe Depalle, Stephen McAdams

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueThe Journal of the Acoustical Society of America · 2016
Typearticle
Languageen
FieldComputer Science
TopicMusic and Audio Processing
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of CanadaCanada Research Chairs
KeywordsModulation (music)Identity (music)SalientAcousticsPitch (Music)PerceptionMusical instrumentCommunicationIdentification (biology)Speech recognitionPsychologyComputer sciencePhysicsArtificial intelligenceNeuroscienceBiology

Abstract

fetched live from OpenAlex

Modulation Power Spectra include dimensions of spectral and temporal modulation that contribute significantly to the perception of musical instrument timbres. Nevertheless, it remains unknown whether each instrument's identity is characterized by specific regions in this representation. A recognition task was applied to tuba, trombone, cello, saxophone, and clarinet sounds resynthesized with filtered spectrotemporal modulations. The most relevant parts of this representation for instrument identification were determined for each instrument. In addition, instruments that were confused with each other led to non-overlapping spectrotemporal modulation regions, suggesting that musical instrument timbres are characterized by specific spectrotemporal modulations.

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 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)0.001
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: Other design · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.750
Threshold uncertainty score0.155

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.022
GPT teacher head0.255
Teacher spread0.233 · 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