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Record W2572054500 · doi:10.1111/desc.12503

Speaking a tone language enhances musical pitch perception in 3–5‐year‐olds

2017· article· en· W2572054500 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueDevelopmental Science · 2017
Typearticle
Languageen
FieldNeuroscience
TopicNeuroscience and Music Perception
Canadian institutionsInstitute for Christian StudiesUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of CanadaNational Natural Science Foundation of ChinaNational Science Foundation
KeywordsPsychologyTone (literature)MusicalPerceptionPitch perceptionPitch (Music)Cognitive psychologyAudiologyCommunicationLinguisticsVisual artsNeuroscience

Abstract

fetched live from OpenAlex

Young children learn multiple cognitive skills concurrently (e.g., language and music). Evidence is limited as to whether and how learning in one domain affects that in another during early development. Here we assessed whether exposure to a tone language benefits musical pitch processing among 3-5-year-old children. More specifically, we compared the pitch perception of Chinese children who spoke a tone language (i.e., Mandarin) with English-speaking American children. We found that Mandarin-speaking children were more advanced at pitch processing than English-speaking children but both groups performed similarly on a control music task (timbre discrimination). The findings support the Pitch Generalization Hypothesis that tone languages drive attention to pitch in nonlinguistic contexts, and suggest that language learning benefits aspects of music perception in early development. A video abstract of this article can be viewed at: https://youtu.be/UY0kpGpPNA0.

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)0.001
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 score0.727
Threshold uncertainty score0.988

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.002
Scholarly communication0.0010.002
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 head0.041
GPT teacher head0.345
Teacher spread0.304 · 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