Noise reduction (NR) algorithms are employed in nearly all commercially available hearing aids to attenuate background noise. However, NR processing also involves undesirable speech distortions, leading to variability in hearing outcomes among individuals with different noise tolerance. Leveraging 30 participants with normal hearing engaged in speech-in-noise tasks, the present study examined whether the cortical measure of neural signal-to-noise ratio (SNR)—the amplitude ratio of auditory evoked responses to target speech onset and noise onset—could predict individual variability in NR outcomes with varying strength, thus serving as a reliable indicator of individual noise tolerance. In addition, we also measured subjective ratings of noise tolerance to see if these measures could capture different perspectives on individual noise tolerance. Results indicated a significant correlation between neural SNR and NR outcomes that intensified with increasing strength of NR processing. While subjective ratings of noise tolerance were not correlated with the neural SNR, noise-tolerance ratings could predict outcomes with stronger NR processing and account for additional variance in the regression model, although the effect was limited. Our findings underscore the importance of accurately assessing an individual’s noise tolerance characteristics in predicting perceptual benefits from various NR processing methods and suggest the advantage of incorporating both cortical and subjective measures in the relevant methodologies.

Background/Objectives: Individuals with similar hearing sensitivity exhibit varying levels of tolerance to background noise, a trait tied to unique individual characteristics that affect their responsiveness to noise reduction (NR) processing in hearing aids. The present study aimed to capture such individual characteristics by employing electrophysiological measures and subjective noise-tolerance profiles, and both were analyzed in relation to speech-in-noise performance and NR outcomes. Methods: From a sample of 42 participants with normal hearing, the neural signal-to-noise ratio (SNR)—a cortical index comparing the amplitude ratio between auditory evoked responses to target speech onset versus noise onset—was calculated, and individual noise-tolerance profiles were also derived using k-means cluster analysis to classify participants into distinct subgroups. Results: The neural SNR showed significant correlations with speech-in-noise performance and NR outcomes with varying strength. In contrast, noise-tolerance subgroups did not show meaningful group-level differences in either speech-in-noise or NR outcomes. The neural SNR and noise-tolerance profiles were found to be statistically independent. Conclusions: While the neural SNR reliably predicted perceptual performance in background noise and NR outcomes, our noise-tolerance profiles lacked sufficient sensitivity. Still, subjective ratings of individual noise tolerance are clinically accessible, and thus, integrating both physiology and subjective measures in the same cohort is a valuable strategy.