Robust End to End Speaker Verification Using EEG

Han, Yan, Krishna, Gautam, Tran, Co, Carnahan, Mason, Tewfik, Ahmed H

arXiv.org Machine Learning 

In this paper we demonstrate that performance of a speaker verification system can be improved by concatenating electroencephalography (EEG) signal features with speech signal. We use state of 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.

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