Neural tracking of the speech envelope predicts binaural unmasking

Abstract

AbstractBinaural unmasking is the remarkable phenomenon that it is substantially easier to detect a signal in noise, when the interaural parameters of the signal are different from those of the noise – a mechanism that comes in handy in so-called cocktail party scenarios. In this study, we investigated the effect of binaural unmasking on neural tracking of the speech envelope. We measured EEG in 8 participants who listened to speech in noise at a fixed signal-to-noise ratio (−12 dB or −9 dB, depending on the speech material), in two conditions: one where speech and noise had the same interaural phase difference (both speech and noise having an opposite waveform across ears,SπNπ), and one where the interaural phase difference of the speech was different from that of the noise (only the speech having an opposite waveform across ears,SπN0). We measured a clear benefit of binaural unmasking in behavioral speech understanding scores, accompanied with increased neural tracking of the speech envelope. Moreover, analyzing the temporal response functions revealed that binaural unmasking also resulted in decreased peak latencies and increased peak amplitudes. Our results are consistent with previous research using auditory evoked potentials and steady-state responses to quantify binaural unmasking at cortical levels. Moreover, they confirm that neural tracking of speech is modulated by speech understanding, even if the acoustic signal-to-noise ratio is kept constant.Significance StatementBinaural unmasking in an important contributing factor to speech understanding in noisy environments. This is the first time that this benefit in speech understanding is measured objectively with EEG. From a clinical perspective, these results could enable the evalu-ation of binaural speech understanding mechanisms in populations for whom behavioral measures are difficult to obtain, such as young children or people with cognitive impair-ment. Moreover, behavioral research has shown that many pathologies (e.g., asymmetric hearing loss, auditory neuropathy, and age-related deficits) are more sensitive to tests that contain a binaural processing component. Our paradigm could enable the detection of such pathologies with an objective approach using neural tracking of speech.