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Record W2601062680 · doi:10.1016/j.bandc.2017.03.010

Preserved appreciation of aesthetic elements of speech and music prosody in an amusic individual: A holistic approach

2017· article· en· W2601062680 on OpenAlexaboutno aff
Ariadne Loutrari, Marjorie Perlman Lorch

Bibliographic record

VenueBrain and Cognition · 2017
Typearticle
Languageen
FieldNeuroscience
TopicNeuroscience and Music Perception
Canadian institutionsnot available
FundersWellcome Trust
KeywordsPsychologyProsodyEmotional prosodyPerceptionPhraseSet (abstract data type)JudgementCognitive psychologyCognitionMusicalMusic psychologyLinguisticsMusic educationNeuroscience

Abstract

fetched live from OpenAlex

We present a follow-up study on the case of a Greek amusic adult, B.Z., whose impaired performance on scale, contour, interval, and meter was reported by Paraskevopoulos, Tsapkini, and Peretz in 2010, employing a culturally-tailored version of the Montreal Battery of Evaluation of Amusia. In the present study, we administered a novel set of perceptual judgement tasks designed to investigate the ability to appreciate holistic prosodic aspects of 'expressiveness' and emotion in phrase length music and speech stimuli. Our results show that, although diagnosed as a congenital amusic, B.Z. scored as well as healthy controls (N=24) on judging 'expressiveness' and emotional prosody in both speech and music stimuli. These findings suggest that the ability to make perceptual judgements about such prosodic qualities may be preserved in individuals who demonstrate difficulties perceiving basic musical features such as melody or rhythm. B.Z.'s case yields new insights into amusia and the processing of speech and music prosody through a holistic approach. The employment of novel stimuli with relatively fewer non-naturalistic manipulations, as developed for this study, may be a useful tool for revealing unexplored aspects of music and speech cognition and offer the possibility to further the investigation of the perception of acoustic streams in more authentic auditory conditions.

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 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 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 score0.924
Threshold uncertainty score0.339

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)0.0000.000

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 head0.157
GPT teacher head0.335
Teacher spread0.178 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations6
Published2017
Admission routes1
Has abstractyes

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