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Record W4400285761 · doi:10.1121/10.0027757

The impact of remote microphones and facial masks on speech production and conversational behaviors in hearing-impaired individuals

2024· article· en· W4400285761 on OpenAlexaff
Menatalla K. Ellag, Jinyu Qian, Ieda Maria Ishida, Ewen MacDonald

Bibliographic record

VenueThe Journal of the Acoustical Society of America · 2024
Typearticle
Languageen
FieldNeuroscience
TopicHearing Loss and Rehabilitation
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsAudiologyPsychologySpeech productionHearing impairedProduction (economics)Speech recognitionComputer scienceMedicine

Abstract

fetched live from OpenAlex

This study investigates the acoustics and conversation behavior of the speech produced during conversations among groups of hearing-impaired individuals. Four groups of four hearing-impaired individuals, all using hearing aids, engaged in discussions on provided topics in the presence of background noise. Conversations were held in four conditions based on two factors (using versus not using a remote microphone; wearing versus not wearing a face mask). Analysis of recorded conversations focused on speech production measures (e.g., fundamental frequency, articulation rate, formant frequencies, etc.) and conversational behaviors (e.g., inter-pausal unit length, floor-transfer offsets, turn duration, etc.). Although both influence the potential difficulty of holding a conversation, distinct effects of mask, remote microphone, and their interaction were observed for measures of speech production and conversational behaviors.

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)0.001
metaresearch head score (Gemma)0.007
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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
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 science0.0000.001
Research integrity0.0000.000
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 head0.025
GPT teacher head0.306
Teacher spread0.281 · 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
Published2024
Admission routes1
Has abstractyes

Explore more

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