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Record W2114803040 · doi:10.1525/mp.2007.25.2.95

Poor-Pitch Singing in the Absence of "Tone Deafness"

2007· article· en· W2114803040 on OpenAlex

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.

Bibliographic record

VenueMusic Perception An Interdisciplinary Journal · 2007
Typearticle
Languageen
FieldNeuroscience
TopicNeuroscience and Music Perception
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsSemitoneSingingImitationPitch perceptionPsychologySpeech recognitionPerceptionRelative pitchTone (literature)AudiologyCommunicationAcousticsComputer scienceLinguisticsSocial psychologyPhysics

Abstract

fetched live from OpenAlex

THE TERM "TONE DEAFNESS," COMMONLY APPLIED TO poor-pitch singing, suggests that the cause lies in faulty perception. However, it is also plausible that problems lie in production, memory, and/or sensorimotor integration. We report the results of two experiments on vocal pitch imitation that addressed these possibilities. Participants listened to and then vocally imitated unfamiliar 4-note pitch sequences.Within each experiment, 10-15% of the participants imitated pitch at least one semitone off and were categorized as "poor-pitch singers." Such deviations were reliable across different pitch classes and therefore constitute transpositions. In addition, poor-pitch singers compressed the size of intervals during production. Poor-pitch singers did not differ from good singers in pitch discrimination accuracy, although they appeared to be hindered rather than helped by singing with correct accompaniment. Taken together, findings suggested that poor-pitch singing results from mismapping of pitch onto action, rather than problems specific to perceptual,motor, or memory systems.

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)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.954
Threshold uncertainty score0.584

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.055
GPT teacher head0.371
Teacher spread0.316 · 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