Audiovisual perception of voicing with age in quiet and cafe noise
Bibliographic record
Abstract
Research has shown that voicing is difficult to discern in noisy environments. While voicing may be difficult to resolve from visual cues, acoustic cues for voicing are relatively robust. This study addresses these factors with normally aging audiovisual perception. Identification responses were gathered with 19–30-year-old and 49–60-year-old adults for audiovisual (AV) CVs differing in voicing and consonant place of articulation. Materials were presented in quiet and in cafe noise (SNR=0 dB) as audio-only (A), visual-only (V), congruent AV, and incongruent AV. Results show a tendency toward use of visual information with age and noise for consonant place of articulation. Notably for voicing, incongruent AV materials that had one voiced component, regardless if it was A or V that was voiced, were consistently perceived as voiced in both age groups and regardless of noise. Only if the A and V components were both voiceless was the syllable perceived as voiceless. These findings indicate the influence of age and noise in the use of perceptual information to identify place of articulation. That voicing is robustly salient from either audio or visual information, despite the unlikely presence of strong visual cues for voicing, indicates a possible bias toward the perception of voicing.
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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 | 0.000 | 0.003 |
| 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 | 0.000 |
| 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".