Evaluating a Deep Neural Noise-Reduction Algorithm for Hearing Aids
Evaluating a Deep Neural Noise-Reduction Algorithm for Hearing Aids in Varying Signal-to-Noise Conditions
Purdue University
50 participants
Oct 16, 2025
INTERVENTIONAL
Conditions
Summary
This study is designed to understand how different hearing-aid noise-reduction technologies affect a listener's ability to hear speech in noisy environments. Participants will listen to speech at several background-noise levels while trying different processing settings. By comparing performance across these conditions, the study aims to identify which types of noise reduction improve speech intelligibility the most. We expect that some noise-reduction strategies will help listeners understand speech better than others, especially in more difficult listening situations.
Eligibility
Inclusion Criteria1
- 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 Criteria4
- Normal hearing
- Severe or profound hearing loss
- Conductive hearing loss
- Neural hearing loss
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Interventions
No neural noise suppression applied. Baseline processing condition.
Neural noise suppression using the lower-strength algorithm parameters.
Neural noise suppression using the higher-strength algorithm parameters.
Noise levels higher than speech levels
Equal speech and noise levels
Speech levels higher than noise levels
Locations(1)
View Full Details on ClinicalTrials.gov
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NCT07287774