Feasibility of Virtual Reality Audiological Testing: Prospective Study
Bibliographic record
Abstract
BACKGROUND: It has been noted in the literature that there is a gap between clinical assessment and real-world performance. Real-world conversations entail visual and audio information, yet there are not any audiological assessment tools that include visual information. Virtual reality (VR) technology has been applied to various areas, including audiology. However, the use of VR in speech-in-noise perception has not yet been investigated. OBJECTIVE: The purpose of this study was to investigate the impact of virtual space (VS) on speech performance and its feasibility to be used as a speech test instrument. We hypothesized that individuals' ability to recognize speech would improve when visual cues were provided. METHODS: A total of 30 individuals with normal hearing and 25 individuals with hearing loss completed pure-tone audiometry and the Korean version of the Hearing in Noise Test (K-HINT) under three conditions-conventional K-HINT (cK-HINT), VS on PC (VSPC), and VS head-mounted display (VSHMD)-at -10 dB, -5 dB, 0 dB, and +5 dB signal-to-noise ratios (SNRs). Participants listened to target speech and repeated it back to the tester for all conditions. Hearing aid users in the hearing loss group completed testing under unaided and aided conditions. A questionnaire was administered after testing to gather subjective opinions on the headset, the VSHMD condition, and test preference. RESULTS: Provision of visual information had a significant impact on speech performance between the normal hearing and hearing impaired groups. The Mann-Whitney U test showed statistical significance (P<.05) between the two groups under all test conditions. Hearing aid use led to better integration of audio and visual cues. Statistical significance through the Mann-Whitney U test was observed for -5 dB (P=.04) and 0 dB (P=.02) SNRs under the cK-HINT condition, as well as for -10 dB (P=.007) and 0 dB (P=.04) SNRs under the VSPC condition, between hearing aid and non-hearing aid users. Participants reported positive responses across almost all items on the questionnaire except for the weight of the headset. Participants preferred a test method with visual imagery, but found the headset to be heavy. CONCLUSIONS: Findings are in line with previous literature that showed that visual cues were beneficial for communication. This is the first study to include hearing aid users with a more naturalistic stimulus and a relatively simple test environment, suggesting the feasibility of VR audiological testing in clinical practice.
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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 | 0.006 |
| 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) | 0.000 | 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 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".