Bibliographic record
Abstract
Figure: Military personnel have to discern and prioritize a barrage of critical information amidst extreme surroundings. © Shutterstock.com/EMLA bomb is exploding, the Humvee is shaking, the radio is blasting, and an officer is listing coordinates over the loudspeaker. Military personnel listen to, transcribe, and respond to audio traffic over numerous channels during their operations. They have to discern and prioritize a barrage of critical information amidst extreme surroundings, which can prove a difficult task. A team of researchers from Defense Research and Development Canada (DRDC), an agency of Canada's Department of National Defense, investigated whether adding a visual signal like a text to an audio message could help the situation. Sharon Abel, PhD, a DRDC defense scientist, presented their findings at the 21st International Congress on Acoustics in Montreal last month. She and her team found that substituting audio messages over the loudspeakers with visual or audiovisual messages resulted in an improvement in speech understanding from 71 percent to 96 percent. “In military operations, it's critical that messages be monitored, encoded, responded to, and relayed accurately [and] in a timely manner to ensure situational awareness, personal safety, and mission success,” Dr. Abel said in a statement. “Our findings suggest that the use of the visual system is a viable supplement for communication in cases of auditory overload or degraded listening.” Researchers conducted two experiments in a mock-up of a military land vehicle to test the value of adding a visual signal to an audio message. First, the team evaluated the benefit of using visual prompts to direct the listener's attention to an audio channel delivering an important message. Participants were played numerous messages in their right and left earphones and over the loudspeakers. The messages were accompanied by different variables, including a backdrop of quiet, vehicle sounds, or babble noise that modeled surrounding conversations, with or without visual cues. Second, they investigated the advantages of texting as a supplement to an audio message by having participants engage in two tasks simultaneously. As participants listened to pairs of phrases in their right and left earphones, they had to determine the accuracy of simple math calculations played over a loudspeaker, as a text message, or through both routes. “Participants had no difficulty responding to messages presented over the headset, although there was a right ear advantage,” Dr. Abel said. “We discovered that messages presented over a loudspeaker in noise were more difficult to understand, but a visual cue directing attention and text messaging resulted in significant improvements in performance.”Figure: Samira AndersonSamira Anderson, PhD, AuD, assistant professor in the Department of Hearing & Speech Sciences at the University of Maryland, said the study makes sense: when people are exposed to multiple messages, they need a way to make the most important ones stick out. The brain identifies an incoming auditory signal as an auditory object so that when a person hears a sound, he or she recognizes what it is, Dr. Anderson said in a phone interview. “Therefore, when a person is receiving and being subjected to competing messages, it's hard for the brain to decide what it wants to pay attention to.” A parallel can be made to watching a movie with captions, where the addition of text can improve a person's understanding of the situation, she added. “The findings show the importance of sensory integration in making sense of the world,” Dr. Anderson said. “The results also speak to the importance of combining several of a person's senses. Usually when we evaluate a sensory system we only evaluate one, but that's not how real life works. People hear and see things together in order to make sense of them.” HJ Return to thehearingjournal.com
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.049 | 0.013 |
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".