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Record W2125306328 · doi:10.1080/02643294.2011.567258

Singing proficiency in congenital amusia: Imitation helps

2010· article· en· W2125306328 on OpenAlexafffund
Alexandra Tremblay‐Champoux, Simone Dalla Bella, Jessica Phillips-Silver, Marie-Andrée Lebrun, Isabelle Peretz

Bibliographic record

VenueCognitive Neuropsychology · 2010
Typearticle
Languageen
FieldNeuroscience
TopicNeuroscience and Music Perception
Canadian institutionsUniversité de MontréalInternational Laboratory for Brain, Music and Sound Research
FundersCanadian Institutes of Health Research
KeywordsSingingImitationPsychologySyllableUnisonLyricsAudiologyMelodyCognitive psychologySpeech recognitionNeuroscienceAcousticsMedicineMusical

Abstract

fetched live from OpenAlex

Singing out of tune characterizes congenital amusia. Here, we examine whether an aid to memory improves singing by studying vocal imitation in 11 amusic adults and 11 matched controls. Participants sang a highly familiar melody on the original lyrics and on the syllable /la/ in three conditions. First, they sang the melody from memory. Second, they sang it after hearing a model, and third, they sang in unison with the model. Results show that amusic individuals benefit from singing by imitation, whether singing after the model or in unison with the model. The amusics who were the most impaired in memory benefited most, particularly when singing on the syllable /la/. Nevertheless, singing remains poor on the pitch dimension; rhythm was intact and unaffected by imitation. These results point to memory as a source of impairment in poor singing, and to imitation as a possible aid for poor singers.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.043
GPT teacher head0.333
Teacher spread0.290 · 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

Citations45
Published2010
Admission routes2
Has abstractyes

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