Bibliographic record
Abstract
The basis for individual differences in the degree to which visual speech input enhances comprehension of acoustically degraded speech is largely unknown. Previous research indicates that fine facial detail is not critical for visual enhancement when auditory information is available; however, these studies did not examine individual differences in ability to make use of fine facial detail in relation to audiovisual speech perception ability. Here, we compare participants based on their ability to benefit from visual speech information in the presence of an auditory signal degraded with noise, modulating the resolution of the visual signal through low-pass spatial frequency filtering and monitoring gaze behavior. Participants who benefited most from the addition of visual information (high visual gain) were more adversely affected by the removal of high spatial frequency information, compared to participants with low visual gain, for materials with both poor and rich contextual cues (i.e., words and sentences, respectively). Differences as a function of gaze behavior between participants with the highest and lowest visual gains were observed only for words, with participants with the highest visual gain fixating longer on the mouth region. Our results indicate that the individual variance in audiovisual speech in noise performance can be accounted for, in part, by better use of fine facial detail information extracted from the visual signal and increased fixation on mouth regions for short stimuli. Thus, for some, audiovisual speech perception may suffer when the visual input (in addition to the auditory signal) is less than perfect.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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 teacher head, 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".