Predicting speech-in-noise ability with static and dynamic auditory figure-ground analysis using structural equation modelling

Abstract

Auditory figure-ground paradigms assess the ability to extract a foreground figure from a random background, a crucial part of central hearing. Previous studies have shown that the ability to extract static figures predicts speech-in-noise ability. In this study, we assessed both fixed and dynamic figures: the latter comprised component frequencies that vary over time like natural speech. We examined how well speech-in-noise ability (for words and sentences) could be predicted by age, peripheral hearing, static and dynamic figure-ground with 159 participants. Regression demonstrated that in addition to audiogram and age, low-frequency dynamic figure-ground accounted for an independent variance of both word- and sentence-in-noise perception, higher than the static figure-ground. The structural equation models showed that a combination of all types of figure-ground tasks and age and audiogram could explain up to 89% of the variance in speech-in-noise, and figure-ground predicted speech-in-noise with a higher effect size than the audiogram or age. Age influenced word perception in noise directly but sentence perception indirectly via effects on peripheral and central hearing. Overall, this study demonstrates that dynamic figure-ground predicts a significant variance in real-life listening better than the prototype figure-ground. The combination of figure-ground tasks predicts real-life listening better than audiogram or age.