Speaker Identification using EEG
This addresses the problem of degraded speaker identification in noisy conditions for audio processing applications, presenting an incremental improvement by integrating EEG data.
The paper tackles speaker identification in noisy environments by using EEG signals, showing that EEG features outperform acoustic features in high background noise and enhance overall system performance.
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.