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Record W2057592692 · doi:10.1121/1.4778355

Patterns in the perception of VC(C)V strings

2002· article· en· W2057592692 on OpenAlexaff
Terrance M. Nearey, Roel Smits

Bibliographic record

VenueThe Journal of the Acoustical Society of America · 2002
Typearticle
Languageen
FieldComputer Science
TopicBlind Source Separation Techniques
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsPerceptMathematicsCombinatoricsClosing (real estate)HomogeneousStatisticsPerceptionPsychology

Abstract

fetched live from OpenAlex

A set of 144 /aC(C)a/ stimuli were constructed (inspired by, e.g., B. Repp, Percept. Psychophys. 24, 471–485 (1978)]). Each consisted of: a vocoid (135 ms steady state followed by 50 ms VC closing transitions); a silent portion; and another vocoid (50 ms CV opening transition plus 250 ms steady state). Four different silent periods [80, 120, 190, and 300 ms] were crossed with six closing transition patterns (ranging from b-like to d-like closures) and with six analogous opening transitions. Thirteen listeners classified each stimulus ten times. Polytomous logistic regression showed that singletons, heterorganic clusters, and geminates all have distinct duration weights. Contrary to expectations, results for place were remarkably simple. Weights for closing transitions show labial closures (/b, bd, bb/) to be widely separated from the coronal closures (/d, db, dd/), but are otherwise homogeneous. Weights for opening cues show a similar dichotomy of labial releases /b, db, bb/ versus coronal releases (/d, bd, dd/); here, however, the singleton /b/ differs slightly from the other labials. A related experiment in Dutch will be discussed and results from both experiments will be compared against proposals from the literature and our own models. [Work supported by SSHRC.].

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.904
Threshold uncertainty score0.298

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0020.000
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 head0.020
GPT teacher head0.261
Teacher spread0.241 · 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 designSimulation or modeling
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

Citations1
Published2002
Admission routes1
Has abstractyes

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