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Record W2009383397 · doi:10.1121/1.4733542

Positional targets for lingual consonants defined using electromagnetic articulography

2012· article· en· W2009383397 on OpenAlexafffundabout
Yana Yunusova, Jeffrey S. Rosenthal, Krista Rudy, Melanie Baljko, John Daskalogiannakis

Bibliographic record

VenueThe Journal of the Acoustical Society of America · 2012
Typearticle
Languageen
FieldPsychology
TopicPhonetics and Phonology Research
Canadian institutionsYork UniversityUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsConsonantVowelTonguePoint (geometry)MathematicsParameterized complexitySpeech recognitionAcousticsComputer scienceLinguisticsPhysicsGeometryCombinatorics

Abstract

fetched live from OpenAlex

The study examined the positional targets for lingual consonants defined using a point-parameterized approach with Wave (NDI, Waterloo, ON, Canada). The overall goal was to determine which consonants had unique tongue positions with respect to other consonants. Nineteen talkers repeated vowel-consonant-vowel (VCV) syllables that included consonants /t, d, s, z, , k, g/ in symmetrical vowel contexts /i, u, a/, embedded in a carrier phrase. Target regions for each consonant, characterized in terms of x,y,z tongue positions at the point of maximum tongue elevation, were extracted. Distances and overlaps were computed between all consonant pairs and compared to the distances and overlaps of their contextual targets. Cognates and postalveolar homorganics were found to share the location of their target regions. On average, alveolar stops showed distinctively different target regions than alveolar fricatives, which in turn showed different target region locations than the postalveolar consonants. Across talker variability in target locations was partially explained by differences in habitual speaking rate and hard palate characteristics.

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 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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.786
Threshold uncertainty score0.311

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.031
GPT teacher head0.341
Teacher spread0.310 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations23
Published2012
Admission routes3
Has abstractyes

Explore more

Same venueThe Journal of the Acoustical Society of AmericaSame topicPhonetics and Phonology ResearchFrench-language works237,207