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Record W2090976858 · doi:10.3389/fpsyg.2011.00120

Congenital Amusia (or Tone-Deafness) Interferes with Pitch Processing in Tone Languages

2011· article· en· W2090976858 on OpenAlexaff
Barbara Tillmann, Denis Burnham, Sébastien Nguyen, Nicolas Grimault, Nathalie Gosselin, Isabelle Peretz

Bibliographic record

VenueFrontiers in Psychology · 2011
Typearticle
Languageen
FieldPsychology
TopicMultisensory perception and integration
Canadian institutionsUniversité de MontréalInternational Laboratory for Brain, Music and Sound Research
Fundersnot available
KeywordsTone (literature)AudiologyPsychologyTone burstNeuroscienceMedicineLinguistics

Abstract

fetched live from OpenAlex

Congenital amusia is a neurogenetic disorder that affects music processing and that is ascribed to a deficit in pitch processing. We investigated whether this deficit extended to pitch processing in speech, notably the pitch changes used to contrast lexical tones in tonal languages. Congenital amusics and matched controls, all non-tonal language speakers, were tested for lexical tone discrimination in Mandarin Chinese (Experiment 1) and in Thai (Experiment 2). Tones were presented in pairs and participants were required to make same/different judgments. Experiment 2 additionally included musical analogs of Thai tones for comparison. Performance of congenital amusics was inferior to that of controls for all materials, suggesting a domain-general pitch-processing deficit. The pitch deficit of amusia is thus not limited to music, but may compromise the ability to process and learn tonal languages. Combined with acoustic analyses of the tone material, the present findings provide new insights into the nature of the pitch-processing deficit exhibited by amusics.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0010.000
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 head0.059
GPT teacher head0.396
Teacher spread0.337 · 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 designObservational
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

Citations95
Published2011
Admission routes1
Has abstractyes

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