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DOI: 10.3766/jaaa.24.9.8
Effects of a Transient Noise Reduction Algorithm on Speech Understanding, Subjective Preference, and Preferred Gain
Publication History
Publication Date:
06 August 2020 (online)
Background: Today's compression hearing aids with noise reduction systems may not manage transient noises effectively because of the short duration of these sounds compared to the onset times of the compressors and/or noise reduction algorithms.
Purpose: The current study was designed to evaluate the effect of a transient noise reduction (TNR) algorithm on listening comfort, speech intelligibility in quiet, and preferred wearer gain in the presence of transients.
Research Design: A single-blinded, repeated-measures design was used.
Study Sample: Thirteen experienced hearing aid users with bilaterally symmetrical (≤7.5 dB) sensorineural hearing loss participated in the study.
Results: Speech identification in quiet (no transient noise) was identical between the TNR On and the TNR Off conditions. The participants showed subjective preference for the TNR algorithm when “comfortable listening” was used as the criterion. Participants preferred less gain than the default prescription in the presence of transient noise sounds. However, the preferred gain was 2.9 dB higher when the TNR was activated than when it was deactivated. This translated to 12.1% improvement in phoneme identification over the TNR Off condition for soft speech.
Conclusions: This study demonstrated that the use of the TNR algorithm would not negatively affect speech identification. The results also suggested that this algorithm may improve listening comfort in the presence of transient noise sounds and ensure consistent use of prescribed gain. Such an algorithm may ensure more consistent audibility across listening environments.