Acoustical Analyses of Conversations Reveal Different Effects of Remote Microphones and Face Masks on Group Conversations by Aided Older Adults
Bibliographic record
Abstract
PURPOSE: This study investigated if changes in speech and conversation behavior by aided individuals with hearing loss could be observed across conditions with versus without the use of a remote microphone while wearing and not wearing a face mask. METHOD: Sixteen hearing aid users were randomly split into four groups of four. Each group engaged in a free-form conversation in the presence of a 55 dBA background noise in each of four conditions. The four conditions were based on combinations of two variables: with versus without a remote microphone and wearing versus not wearing a face mask. The recordings of the conversations were analyzed to compare measures of speech production and conversational behavior across conditions. RESULTS: Conversations with a remote microphone exhibited shorter average floor transfer offsets (FTOs) and longer conversation durations. In conversations where masks were worn, the average fundamental frequency produced by talkers was lower. A complex interaction was observed in the influence of remote microphone and face mask on the average length of connected utterances. CONCLUSIONS: Acoustic analysis of speech production and conversational behavior can be used to evaluate the benefit of hearing assistive technology. The observed differences in behavior when using a remote microphone are consistent with reduced listening effort. The differences observed when wearing a face mask are all consistent with increased resistance to airflow and the consequent effects on speech production rather than increased listening difficulty.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".