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Record W4229441788 · doi:10.1121/10.0010667

Effect of speech-related smile suppression on emotional valence

2022· article· en· W4229441788 on OpenAlexaff
Nicole Ebbutt, Kyra Hung, Magdalena Ivok, Charissa Purnomo, Farhan Samir, Gillian de Boer, Bryan Gick

Bibliographic record

VenueThe Journal of the Acoustical Society of America · 2022
Typearticle
Languageen
FieldMedicine
TopicFacial Nerve Paralysis Treatment and Research
Canadian institutionsSimon Fraser UniversityUniversity of British Columbia
Fundersnot available
KeywordsPsychologySentenceValence (chemistry)AudiologySet (abstract data type)Facial expressionCognitive psychologyCommunicationLinguisticsMedicineComputer science

Abstract

fetched live from OpenAlex

The physical act of smiling has direct positive effects on mood [Kleinke et al., Pers. Soc. Psychol. 74, 272–279 (1998)]. Relatedly, Rummer et al. [Emotion, 14(2), 246–250 (2014)] observed that participants rated comics as funnier if they had just produced /i/ (which requires adopting a smile-like position) than if they produced /o/. The present study tests whether suppression of smile posture by speech movements can cause individuals to view a subject less positively. To do so, we ask participants to maintain a smile while we present a series of visual stimuli labeled with target and control sounds. Bilabial sounds are targeted as Liu et al. found that bilabial stops (/p/ and /b/) suppress smile posture [ISSP12, 130–133 (2021)]. After articulating a sound that either suppresses or does not suppress their smile posture, participants rate each image set on a measure of emotion. Results will be presented and discussed bearing on the prediction that in the smile condition, participants will rate the image as less positive if they have just produced a sentence which includes a bilabial stop. [Work supported by NIH and NSERC.]

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 score0.342
Threshold uncertainty score0.818

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.012
GPT teacher head0.306
Teacher spread0.294 · 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

Citations0
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueThe Journal of the Acoustical Society of AmericaSame topicFacial Nerve Paralysis Treatment and ResearchFrench-language works237,207