Restoration and Efficiency of the Neural Processing of Continuous Speech Are Promoted by Prior Knowledge

Sufficiently noisy listening conditions can completely mask the acoustic signal of significant parts of a sentence, and yet listeners may still report the perception of hearing the masked speech. This occurs even when the speech signal is removed entirely, if the gap is filled with stationary noise, a phenomenon known as perceptual restoration. At the neural level, however, it is unclear the extent to which the neural representation of missing extended speech sequences is similar to the dynamic neural representation of ordinary continuous speech. Using auditory magnetoencephalography (MEG), we show that stimulus reconstruction, a technique developed for use with neural representations of ordinary speech, works also for the missing speech segments replaced by noise, even when spanning several phonemes and words. The reconstruction fidelity of the missing speech, up to 25% of what would be attained if present, depends however on listeners’ familiarity with the missing segment. This same familiarity also speeds up the most prominent stage of the cortical processing of ordinary speech by approximately 5 ms. Both effects disappear when listeners have no or little prior experience with the speech segment. The results are consistent with adaptive expectation mechanisms that consolidate detailed representations about speech sounds as identifiable factors assisting automatic restoration over ecologically relevant timescales.