  In this paper we explore speaker identification using electroencephalography
(EEG) signals. The performance of speaker identification systems degrades in
presence of background noise, this paper demonstrates that EEG features can be
used to enhance the performance of speaker identification systems operating in
presence and absence of background noise. The paper further demonstrates that
in presence of high background noise, speaker identification system using only
EEG features as input demonstrates better performance than the system using
only acoustic features as input.
