Trying a deep-learning noise-reduction feature for hearing aids
Official title: Evaluating a Deep Neural Noise-Reduction Algorithm for Hearing Aids in Varying Signal-to-Noise Conditions
Run by Purdue University · NCT07287774 · Data updated 2026-11-12
This test tries a deep-learning noise-reduction feature in hearing aids to see if it helps people with mild-to-moderate cochlear hearing loss understand speech in noisy places.
Quick facts
| Study type | Interventional |
|---|---|
| Ages | 18 Years and up |
| Sex | All |
| Enrollment | 50 (estimated) |
| Sponsor | Purdue University Academic / other |
| Locations | 1 site (West Lafayette, Indiana) |
| Status | Recruiting |
| Started | October 16, 2025 |
| Main results expected | April 30, 2026 |
| Study ends | April 30, 2026 |
| Registry record updated | December 17, 2025 |
| Trial ID | NCT07287774 on ClinicalTrials.gov |
Is this trial a fit for you?
✓Likely a good fit
Ideal candidates are hearing-aid candidates with mild-to-moderate cochlear (sensorineural) hearing loss, especially with higher-frequency loss and who have difficulty understanding speech in noise.
✕Probably not a fit
People with normal hearing, severe or profound hearing loss, conductive hearing loss, or neural hearing loss are unlikely to benefit from or qualify for this test.
A plain-English reading of the study's rules. Only the study team can confirm whether you qualify.
What this trial studies
Participants with mild-to-moderate cochlear hearing loss will listen to speech stimuli presented with various levels of background noise while wearing a hearing-aid configuration that isolates single-microphone noise-reduction. The study compares several processing modes (no noise reduction, low, and high DNN-based noise reduction) across multiple signal-to-noise ratios to represent easier and harder listening conditions. All participants experience every condition in a counterbalanced order to limit order effects, and speech intelligibility is measured under each setting. The monaural, omnidirectional setup removes directional microphone benefits so the effects of the noise-reduction algorithms can be isolated.
Why it matters
Potential benefit: If successful, this approach could help some listeners understand speech better in noisy everyday settings and reduce listening effort.
How similar studies have gone: Prior research has shown that DNN-based noise-reduction can improve speech clarity for some listeners, but benefits vary with noise type, SNR, and individual hearing profiles.
Who can join: the full rules
Show full inclusion / exclusion criteria
Inclusion Criteria: * A hearing aid candidate with mild-to-moderate cochlear hearing loss, based on audiometric profile (at least 20 dB of hearing loss at 2000 Hz, with progressively worse hearing levels at higher frequencies). Exclusion Criteria: * Normal hearing * Severe or profound hearing loss * Conductive hearing loss * Neural hearing loss
Where it's running
-
Purdue University
West Lafayette, Indiana, United States Recruiting
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How to take part
- Review the eligibility criteria above with your treating physician.
- Check the official listing on ClinicalTrials.gov for the latest contact details and recruitment status.
- Contact the study coordinator or principal investigator to ask for pre-screening. Pre-screening is free and never obligates you to enroll.