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Record W7118224044

Visual Perception of Gravity: Effect on Speech Tongue Posture

2025· other· en· W7118224044 on OpenAlexvenueno aff
Masha Chernets, Victor Wong, Jahurul Islam, Zoë Cheng, Tiana Ho, Bryan Gick

Bibliographic record

VenueCanadian acoustics · 2025
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsFalling (accident)TonguePerceptionIllusionSpeech productionBalance (ability)Vestibular system
DOInot available

Abstract

fetched live from OpenAlex

Visual perception of gravity change may impact tongue posture during speech production. Previous studies [Chander et al., 2019, Behav. Sci., 9(11)] report anticipatory visual disturbances inducing compensatory postural behavior in the human body [Philips et al., 2022, Theor. Iss. Ergon. Sci., 23, 25] and, furthermore, showed the magnitude of such postural responses is dependent on velocity and direction of visual perception. Assländer et al. [2023, Sci. Rep., 13, 2594] investigated the visual component impact on body posture balance in virtual reality (VR). An earlier VR study on tongue posture [Chernets et al., 2024, JASA 156] found that posture significantly differed between visually perceived falling vs. rising, and levelled vs. rising gravitational conditions; however, there was inter-participant variation in the direction of tongue posture change with no generalizable consistent directional change across participants. The current study investigates tongue posture in speech production during perceived gravity changes in an immersive VR environment. Ultrasound imaging is used to measure tongue posture changes during speech production compared to a non-speech condition while experiencing a VR plank-walk in gravitationally stable and falling conditions. Furthermore, within the falling condition posture is separated into weightless falling (initial and midpoint of fall) vs. force of fall (endpoint of fall). Acoustic analyses compare the production of an elongated vowel, nonsense CVC sequences, and CVC word sequences across conditions. We predict that the falling condition will induce postural adjustment for vowels, resulting in different tongue postures between the falling and level conditions. Results will be presented for a post-trial immersion questionnaire investigating a possible correlation between reported level of VR immersion and degree of tongue posture compensation, as well as for acoustic and articulatory analyses. Implications for postural adaptation in VR and real environments will be discussed.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.005
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.000

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 head0.005
GPT teacher head0.260
Teacher spread0.255 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2025
Admission routes1
Has abstractyes

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