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Record W2327070458 · doi:10.5539/ijel.v6n2p131

Production and Interaction between Gesture and Speech: A Review

2016· review· en· W2327070458 on OpenAlexvenueno aff
Ying Gao, Yuqin Liu, Chunyue Zhou

Bibliographic record

VenueInternational Journal of English Linguistics · 2016
Typereview
Languageen
FieldPsychology
TopicHearing Impairment and Communication
Canadian institutionsnot available
FundersFundamental Research Funds for the Central Universities
KeywordsGestureComputer scienceConsistency (knowledge bases)Focus (optics)Speech productionProduction (economics)Speech recognitionGesture recognitionNatural language processingArtificial intelligence

Abstract

fetched live from OpenAlex

<p>Gesture in multimodal researches has been studied widely recently, and how gesture interacts with speech in communication is the focus in most researches. Some hypotheses or models about production and interaction between gesture and speech are introduced and compared in this paper. We find that it is generally agreed that speech production mechanism can be explained based on Levelt’s Model; while there is no consistency about gesture production and the interaction between gesture and speech. Most of theories argue that gesture stems from the visual-spatial images in working memory; some models approve of the interactive relationship while others consider no interaction between gesture and speech. Further research will be made in the areas of theoretical and applicative aspects.</p>

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)0.047
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.982
Threshold uncertainty score0.961

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.047
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.085
GPT teacher head0.430
Teacher spread0.344 · 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.

Study designOther design
Domainnot available
GenreReview

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
Published2016
Admission routes1
Has abstractyes

Explore more

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