EEG alpha power as a measure of listening effort reduction in adverse conditions
* Presenting author
Noise levels in everyday environments are typically low enough for speech comprehension, but over extended periods of time, listeners may experience fatigue. We measured the neurocognitive compensation required to separate speech from noise – listening effort – using electroencephalography, for unprocessed and AdaptDRC-enhanced speech. AdaptDRC is a noise-dependent near-end-listening-enhancement algorithm which significantly improves the intelligibility of speech in noise and reduces subjectively rated listening effort (Rennies et al., 2018).Participants (N=27) completed a listening effort task using a categorical listening effort scale, in which sentences were presented at five SNRs and in two types of noise. We also measured speech intelligibility, hearing levels, and cognitive abilities. Subjective listening effort was significantly lower, and speech intelligibility was significantly higher for AdaptDRC speech than unprocessed speech (p<.001). Analyses of the neurophysiological data show that there is a non-linear relationship between SNR and spectral alpha power with a peak between 0-5dB, and that alpha power is sensitive to noise type and speech processing. Better working memory and selective attention scores predict lower subjective listening effort ratings. These findings provide insight into the neurophysiological correlates of listening effort and aid the development of an objective measure of cognitive load for speech in noise.