Evaluating a Deep Neural Noise-Reduction Algorithm for Hearing Aids

Recruiting now · Not applicable

Conditions studied: Hearing Loss, Cochlear

In brief

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.

Key facts

Study ID

NCT07287774

Run by

Purdue University

People needed

50

Starts

2025-10-16

Expected to finish

2026-04-30

Last updated by the study team

2025-12-17

Who can join

Age: 18 and older. Sex: any. Healthy volunteers: not accepted.

You may qualify if…

• 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).

You may not qualify if…

• Normal hearing
• Severe or profound hearing loss
• Conductive hearing loss
• Neural hearing loss

Where it is running

• Purdue University — West Lafayette, Indiana, United States (enrolling)

Full record on ClinicalTrials.gov

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