Christi W Miller1, Ruth A Bentler2, Yu-Hsiang Wu2, James Lewis3, Kelly Tremblay1. 1. a Department of Speech and Hearing Sciences , University of Washington , Seattle , WA , USA. 2. b Department of Communication Sciences and Disorders , University of Iowa , Iowa City , IA , USA , and. 3. c Department of Audiology and Speech Pathology , University of Tennessee Health Science Center , Knoxville , TN , USA.
Abstract
OBJECTIVE: The aims of this study were to: 1) quantify the amount of change in signal-to-noise ratio (SNR) as a result of compression and noise reduction (NR) processing in devices from three hearing aid (HA) manufacturers and 2) use the SNR changes to predict changes in speech perception. We hypothesised that the SNR change would differ across processing type and manufacturer, and that improvements in SNR would relate to improvements in performance. DESIGN: SNR at the output of the HAs was quantified using a phase-inversion technique. A linear mixed model was used to determine whether changes in SNR across HA conditions were predictive of changes in aided speech perception in noise. STUDY SAMPLE: Two groups participated: 25 participants had normal-hearing and 25 participants had mild to moderately severe sensorineural hearing loss. RESULTS: The HAs programmed for both groups changed the SNR by a small, but statistically significant amount. Significant interactions in SNR changes were observed between HA devices and processing types. However, the change in SNR was not predictive of changes in speech perception. CONCLUSION: Although observed significant changes in SNR resulting from compression and NR did not convert to changes in speech perception, these algorithms may serve other purposes.
OBJECTIVE: The aims of this study were to: 1) quantify the amount of change in signal-to-noise ratio (SNR) as a result of compression and noise reduction (NR) processing in devices from three hearing aid (HA) manufacturers and 2) use the SNR changes to predict changes in speech perception. We hypothesised that the SNR change would differ across processing type and manufacturer, and that improvements in SNR would relate to improvements in performance. DESIGN: SNR at the output of the HAs was quantified using a phase-inversion technique. A linear mixed model was used to determine whether changes in SNR across HA conditions were predictive of changes in aided speech perception in noise. STUDY SAMPLE: Two groups participated: 25 participants had normal-hearing and 25 participants had mild to moderately severe sensorineural hearing loss. RESULTS: The HAs programmed for both groups changed the SNR by a small, but statistically significant amount. Significant interactions in SNR changes were observed between HA devices and processing types. However, the change in SNR was not predictive of changes in speech perception. CONCLUSION: Although observed significant changes in SNR resulting from compression and NR did not convert to changes in speech perception, these algorithms may serve other purposes.