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Accuracy Assessment for AG500, Electromagnetic Articulograph

2008· article· en· W2044383628 on OpenAlexaff
Yana Yunusova, Jordan R. Green, Antje S. Mefferd

Bibliographic record

VenueJournal of Speech Language and Hearing Research · 2008
Typearticle
Languageen
FieldPsychology
TopicPhonetics and Phonology Research
Canadian institutionsUniversity of Toronto
FundersNational Institute on Deafness and Other Communication Disorders
KeywordsPsychologyAudiologyPhysicsMedicine

Abstract

fetched live from OpenAlex

PURPOSE: The goal of this article was to evaluate the accuracy and reliability of the AG500 (Carstens Medizinelectronik, Lenglern, Germany), an electromagnetic device developed recently to register articulatory movements in three dimensions. This technology seems to have unprecedented capabilities to provide rich information about time-varying positions of articulators. However, strengths and weaknesses of the system need to be better understood before the device is used for speech research. METHOD: Evaluations of the sensor positions over time were obtained during (a) movements of the calibration device, (b) manual movements of sensors in a cartridge within the recording field of the cube, and (c) various speech tasks. RESULTS: Results showed a median error to be under 0.5 mm across different types of recordings. The maximum error often ranged between 1 and 2 mm. The magnitude of error depended somewhat on the task but largely on the location of the sensors within the recording region of the cube. CONCLUSION: The performance of the system was judged as adequate for speech movement acquisition, provided that specific steps are taken for minimizing error during recording and for validating the quality of recorded data.

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)0.003
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.889
Threshold uncertainty score0.573

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.107
GPT teacher head0.471
Teacher spread0.364 · 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 designObservational
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

Citations108
Published2008
Admission routes1
Has abstractyes

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