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Record W2134031337 · doi:10.1080/14015430050175860

Formal perceptual evaluation of voice quality in the United Kingdom

2000· article· en· W2134031337 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

VenueLogopedics Phoniatrics Vocology · 2000
Typearticle
Languageen
FieldMedicine
TopicVoice and Speech Disorders
Canadian institutionsSt. Thomas Hospital
Fundersnot available
KeywordsTerminologyPerceptionQuality (philosophy)Reliability (semiconductor)Computer scienceVariety (cybernetics)Position statementScheme (mathematics)Statement (logic)Speech recognitionSound qualityProblem statementVoice analysisPsychologyArtificial intelligenceMedicineLinguisticsManagement scienceEngineeringMathematics

Abstract

fetched live from OpenAlex

This document is a position statement on the formal perceptual evaluation of voice quality in the United Kingdom (UK). It addresses a number of clinical issues pertaining to the complexity of voice quality analysis. There is also a brief description of the three formal perceptual protocols most commonly used in the UK: The Vocal Profile Analysis (VPA), GRBAS and The Buffalo III Voice Profile. Potential clinical problems with perceptual voice quality evaluation are highlighted. Problems associated with the lack of defined terminology, limitless variety of voice quality, general lack of reliability data and difficulties in determining specificity and sensitivity are discussed. A practical guide for selecting an evaluation scheme is described. The conclusion is that the GRBAS scheme should be recommended as the absolute minimum standard for practising UK voice clinicians. However, there is a clear need to develop a more satisfactory perceptual rating scheme that is clinically realistic, theoretically sound, internationally acceptable and has proven reliability.

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)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.220
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.109
GPT teacher head0.396
Teacher spread0.287 · 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