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Record W4244008181 · doi:10.1017/s0008413100003650

There Are No Back Vowels: The Larygeal Articulator Model

2005· article· en· W4244008181 on OpenAlexaff
John H. Esling

Bibliographic record

VenueThe Canadian Journal of Linguistics / La revue canadienne de linguistique · 2005
Typearticle
Languageen
FieldPsychology
TopicPhonetics and Phonology Research
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsArticulatorVocal tractVowelGesturePhonologyLinguisticsPsychologySpeech recognitionComputer scienceArtificial intelligenceMedicineOrthodontics

Abstract

fetched live from OpenAlex

Abstract As an alternative to the high-low-front-back model of vowel specification, the laryngeal articulator model is proposed, based on a reinterpretation of how the vocal tract functions to produce laryngeal and pharyngeal sounds. Evidence drawn from numerous laryngoscopic studies demonstrates the scope of articulatory behaviours possible in the pharynx. For a broad sample of languages, lingual retraction is shown to accompany laryngeal/pharyngeal gestures, motivating the redistribution of vowel quality designations. The vocal tract is divided into two articulatory components: the laryngeal articulator and the oral articulator. The vowel chart is split into three sectors: front, raised, and retracted. Whereas front vowels can be qualified as close or open, so-called back vowels are re-designated as either raised or retracted, and the role of retraction as a function of the laryngeal constrictor mechanism is elaborated.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.008
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.002
Scholarly communication0.0040.003
Open science0.0010.002
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0080.003

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 head0.028
GPT teacher head0.295
Teacher spread0.267 · 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 designTheoretical or conceptual
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

Citations7
Published2005
Admission routes1
Has abstractyes

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Same venueThe Canadian Journal of Linguistics / La revue canadienne de linguistiqueSame topicPhonetics and Phonology ResearchFrench-language works237,207