  In this paper we demonstrate that performance of a speaker verification
system can be improved by concatenating electroencephalography (EEG) signal
features with speech signal features or only using EEG signal features. We use
state-of-the-art end-to-end deep learning model for performing speaker
verification and we demonstrate our results for noisy speech. Our results
indicate that EEG signals can improve the robustness of speaker verification
systems, especially in noiser environment.
