The Effects of Static and Moving Spectral Ripple Sensitivity on Unaided and Aided Speech Perception in Noise.

ABSTRACT

Purpose: This study evaluated whether certain spectral ripple conditions were more informative than others in predicting ecologically relevant unaided and aided speech outcomes. Method: A quasi-experimental study design was used to evaluate 67 older adult hearing aid users with bilateral, symmetrical hearing loss. Speech perception in noise was tested under conditions of unaided and aided, auditory-only and auditory-visual, and 2 types of noise. Predictors included age, audiometric thresholds, audibility, hearing aid compression, and modulation depth detection thresholds for moving (4-Hz) or static (0-Hz) 2-cycle/octave spectral ripples applied to carriers of broadband noise or 2000-Hz low- or high-pass filtered noise. Results: A principal component analysis of the modulation detection data found that broadband and low-pass static and moving ripple detection thresholds loaded onto the first factor whereas high-pass static and moving ripple detection thresholds loaded onto a second factor. A linear mixed model revealed that audibility and the first factor (reflecting broadband and low-pass static and moving ripples) were significantly associated with speech perception performance. Similar results were found for unaided and aided speech scores. The interactions between speech conditions were not significant, suggesting that the relationship between ripples and speech perception was consistent regardless of visual cues or noise condition. High-pass ripple sensitivity was not correlated with speech understanding. Conclusions: The results suggest that, for hearing aid users, poor speech understanding in noise and sensitivity to both static and slow-moving ripples may reflect deficits in the same underlying auditory processing mechanism. Significant factor loadings involving ripple stimuli with low-frequency content may suggest an impaired ability to use temporal fine structure information in the stimulus waveform. Support is provided for the use of spectral ripple testing to predict speech perception outcomes in clinical settings.