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Record W2606954870 · doi:10.1017/s0025100317000159

Revisions to the VoQS system for the transcription of voice quality

2017· article· en· W2606954870 on OpenAlexaff
Martin J. Ball, John H. Esling, B. Craig Dickson

Bibliographic record

VenueJournal of the International Phonetic Association · 2017
Typearticle
Languageen
FieldComputer Science
TopicSpeech Recognition and Synthesis
Canadian institutionsUniversity of Victoria
FundersBangor University
KeywordsPhonationTranscription (linguistics)Section (typography)LarynxQuality (philosophy)Speech recognitionComputer scienceChartCommunicationPsychologyAudiologyLinguisticsMedicineMathematicsStatistics

Abstract

fetched live from OpenAlex

The ‘voice quality symbols’ (VoQS) transcription system for voice quality was introduced some 20 years ago, and no major revision has been undertaken since then. In this account we describe the first major revision of the VoQS chart, these changes being mostly in the form of additions to the section on phonation types, but include also changes to the layout of the supralaryngeal settings section. These reflect recent developments in the understanding of the physiological underpinnings of sounds produced in the larynx including certain phonation types.

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)0.016
metaresearch head score (Gemma)0.076
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.049
Threshold uncertainty score0.166

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0160.076
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.003
Science and technology studies0.0010.002
Scholarly communication0.0050.003
Open science0.0020.003
Research integrity0.0020.006
Insufficient payload (model declined to judge)0.0490.062

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 head0.046
GPT teacher head0.319
Teacher spread0.273 · 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 designNot applicable
Domainnot available
GenreMethods

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

Citations27
Published2017
Admission routes1
Has abstractyes

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