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Record W4405080442 · doi:10.1177/23312165241296073

Conversational Dynamics in Task Dialogue Between Interlocutors With and Without Hearing Impairment

2024· article· en· W4405080442 on OpenAlexaff
A. Josefine Munch Sørensen, Thomas Lunner, Ewen MacDonald

Bibliographic record

VenueTrends in Hearing · 2024
Typearticle
Languageen
FieldPsychology
TopicHearing Impairment and Communication
Canadian institutionsUniversity of Waterloo
FundersWilliam Demant Fonden
KeywordsAudiologyPsychologyQUIETHearing aidNoise (video)Hearing impairedTask (project management)Hearing lossMedicineComputer science

Abstract

fetched live from OpenAlex

This study investigated the effects of noise and hearing impairment on conversational dynamics between pairs of young normal-hearing and older hearing-impaired interlocutors. Twelve pairs of normal-hearing and hearing-impaired individuals completed a spot-the-difference task in quiet and in three levels of multitalker babble. To achieve the rapid response timing of turn taking that has been observed in normal conversations, people must simultaneously comprehend incoming speech, plan a response, and predict when their partners will end their turn. In difficult conditions, we hypothesized that the timing of turn taking by both normal-hearing and hearing-impaired interlocutors would be delayed and more variable. We found that the timing of turn starts by talkers with hearing impairment had higher variability than those with normal hearing, and participants with both normal hearing and hearing impairment started turns later and with more variability in the presence of noise. Overall, in the presence of noise, talkers spoke louder and slower, increased the duration of their pauses but decreased their rate of occurrence, and produced longer interpausal units, that is, units of connected speech surrounded by silence. However, when compared to previous studies of conversations between normal-hearing partners, the pattern of changes in conversational behavior by the normal-hearing participants was very different in the most challenging noise condition. The extent to which these adaptations are made to reduce the difficulty experienced by their partner with hearing impairment vs. the difficulty they experience themselves is not clear.

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)0.000
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.049
Threshold uncertainty score0.575

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0000.000
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 head0.050
GPT teacher head0.348
Teacher spread0.299 · 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

Citations7
Published2024
Admission routes1
Has abstractyes

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