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Record W2902832493 · doi:10.1159/000493755

Microtonal Variation in Sung Cantonese

2018· article· en· W2902832493 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.

Bibliographic record

VenuePhonetica · 2018
Typearticle
Languageen
FieldPsychology
TopicPhonetics and Phonology Research
Canadian institutionsUniversity of British Columbia
FundersNational Institute on Deafness and Other Communication DisordersNational Institutes of Health
KeywordsVariation (astronomy)Speech recognitionMathematicsLinguisticsNatural language processingComputer sciencePhilosophyPhysics

Abstract

fetched live from OpenAlex

BACKGROUND/AIMS: Both music and language impose constraints on fundamental frequency (F0) in sung music. Composers are known to set words of tone languages to music in a way that reflects tone height but fails to include tone contour. This study tests whether choral singers add linguistic tone contour information to an unfamiliar song by examining whether Cantonese singers make use of microtonal variation. METHODS: 12 native Cantonese-speaking non-professional choral singers learned and sang a novel song in Cantonese which included a minimal set of the Cantonese tones to probe whether everyday singers add in missing contour information. RESULTS: Cantonese singers add in a rising F0 contour of less than a semitone when singing syllables with lexical rising tones. This microtonal variation is not observed when singing in a lower register. CONCLUSION: Cantonese singers use microtonal contours to reflect rising contours of Cantonese linguistic tones.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.889
Threshold uncertainty score0.997

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 communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0090.003

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 head0.030
GPT teacher head0.370
Teacher spread0.340 · 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