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Record W1969168190 · doi:10.7202/1014393ar

On the Role of Vocal Idioms in Singing

2013· article· en· W1969168190 on OpenAlexvenueno aff
James A. Stark

Bibliographic record

VenueCanadian University Music Review · 2013
Typearticle
Languageen
FieldArts and Humanities
TopicDiverse Musicological Studies
Canadian institutionsnot available
Fundersnot available
KeywordsSingingArticulation (sociology)Tone (literature)Variety (cybernetics)CriticismLinguisticsPsychologyComputer scienceArtAcousticsLiteraturePhilosophyArtificial intelligence

Abstract

fetched live from OpenAlex

The identification of particular vocal techniques in singing, which combine to form distinctive vocal idioms, is important for an understanding of both "classical" and "vernacular" musical styles. The modern critical literature on song is based largely on the limited concept of a "word-tone relationship," with musico-poetic synthesis as its ideal. Performance practices are as important to song criticism as is the study of written scores. The elements of voice quality and vocal articulation, with specific reference to the physiology and acoustics of the human voice, provide the analytical tools for defining vocal idioms and their role in the value and success of a song. The description of such idioms requires a rapprochement between vocal history, pedagogy, and science. Using the bel canto paradigm as a reference point, this article discusses a variety of vocal idioms. Gluck's aria, "Che farò senza Euridice" is used to illustrate how an understanding of vocal idioms can alter our judgment of a piece which has sometimes been condemned for its poor word-tone relationship.

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)0.003
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.144
Threshold uncertainty score0.287

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0050.005
Science and technology studies0.0030.016
Scholarly communication0.0040.003
Open science0.0010.002
Research integrity0.0010.002
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 head0.061
GPT teacher head0.172
Teacher spread0.111 · 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 designQualitative
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

Citations2
Published2013
Admission routes1
Has abstractyes

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