Speech-reception-threshold estimation via EEG-based continuous speech envelope reconstruction

Abstract

This study investigates the potential of speech-reception-threshold (SRT) estimation through electroencephalography (EEG) based envelope reconstruction techniques with continuous speech. Additionally, we investigate the influence of the stimulis signal-to-noise ratio (SNR) on the temporal response function (TRF). Twenty young normal-hearing participants listened to audiobook excerpts with varying background noise levels while EEG was recorded. A linear decoder was trained to reconstruct the speech envelope from the EEG data. The reconstruction accuracy was calculated as the Pearsons correlation between the reconstructed and actual speech envelopes. An EEG SRT estimate (SRTneuro) was obtained as the midpoint of a sigmoid function fitted to the reconstruction accuracy versus SNR data points. Additionally, the TRF was estimated at each SNR level, followed by a statistical analysis to reveal significant effects of SNR levels on the latencies and amplitudes of the most prominent components. The SRTneuro was within 3 dB of the behavioral SRT for all participants. The TRF analysis showed a significant latency decrease for N1 and P2 and a significant amplitude magnitude increase for N1 and P2 with increasing SNR. The results suggest that both envelope reconstruction accuracy and the TRF components are influenced by changes in SNR, indicating they may be linked to the same underlying neural process.