Effects of vision, listener head movement, and target location on spatial selective auditory attention
Bibliographic record
Abstract
Listeners can use spatial selective auditory attention (SSAA) to focus on one talker in a complex acoustic scene. We have reported [Macpherson & Ellis, ASA Salt Lake, 2016] that listeners’ ability to attend to a frontal target in the presence of spatially separated distractors is decreased in a head-movement condition, suggesting that listeners cannot rapidly update the focus of their SSAA to compensate fully for head motion. Participants reported anecdotally that being able to see the target loudspeaker seemed beneficial in directing SSAA. Here, we assessed the benefit of access to a visual reference frame in a similar task. Under lighted and dark conditions, on each trial, listeners either fixated toward 0 azimuth or oscillated their heads at ~0.5 Hz with an amplitude of ~±40 degrees while five different simultaneous equal-intensity sequences of four spoken digits were presented as target (at azimuths from 0 to 90 degrees) and four distractors (at azimuths ±22.5 and ±45 degrees relative to the central target). Listeners verbally reported the target sequence heard. Performance declined under head motion and with increasing target eccentricity, but not additionally in dark conditions, suggesting that a visual reference frame was not beneficial in directing SSAA in our task.
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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 | 0.004 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".