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Record W2051327655 · doi:10.1037/a0029046

Vibrotactile discrimination of musical timbre.

2012· article· en· W2051327655 on OpenAlex
Frank Russo, Paolo Ammirante, Deborah I. Fels

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

VenueJournal of Experimental Psychology Human Perception & Performance · 2012
Typearticle
Languageen
FieldNeuroscience
TopicTactile and Sensory Interactions
Canadian institutionsToronto Metropolitan University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsTimbrePitch (Music)AudiologyDuration (music)Musical instrumentMasking (illustration)PianoPsychologyAcousticsSpeech recognitionMusicalComputer sciencePerceptionPhysicsArtNeuroscienceMedicine

Abstract

fetched live from OpenAlex

Five experiments investigated the ability to discriminate between musical timbres based on vibrotactile stimulation alone. Participants made same/different judgments on pairs of complex waveforms presented sequentially to the back through voice coils embedded in a conforming chair. Discrimination between cello, piano, and trombone tones matched for F0, duration, and magnitude was above chance with white noise masking the sound output of the voice coils (Experiment 1), with additional masking to control for bone-conducted sound (Experiment 2), and among a group of deaf individuals (Experiment 4a). Hearing (Experiment 3) and deaf individuals (Experiment 4b) also successfully discriminated between dull and bright timbres varying only with regard to spectral centroid. We propose that, as with auditory discrimination of musical timbre, vibrotactile discrimination may involve the cortical integration of filtered output from frequency-tuned mechanoreceptors functioning as critical bands.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
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 score0.154
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.087
GPT teacher head0.399
Teacher spread0.311 · 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