Speaker Identification using EEG

2020/03/07 by Gautam Krishna, Co Tran, Krishna, Gautam +6
Computer Science · Engineering · Mathematics · #Audio and Speech Processing (eess.AS) #Blind Source Separation Techniques #FOS: Computer and information sciences #FOS: Electrical engineering #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Signal Processing (eess.SP) #Sound (cs.SD) #Speech Recognition and Synthesis #Speech and Audio Processing #cs.LG #cs.SD #eess.AS #eess.SP #electronic engineering #information engineering #stat.ML

paper · pdf · doi:10.48550/arxiv.2003.04733

arxiv created 2020/03/07 · openalex publication_date 2020/03/07 · arxiv updated 2020/03/11 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

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.

Citations

• Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modeling
• Deep Speaker: an End-to-End Neural Speaker Embedding System
• An Empirical Evaluation of Generic Convolutional and Recurrent Networks for Sequence Modeling
• Voice Activity Detection in presence of background noise using EEG

Related

• Robust End-to-End Speaker Verification Using EEG
• Speech Recognition with no speech or with noisy speech
• Voice Activity Detection in presence of background noise using EEG
• EEG-Derived Voice Signature for Attended Speaker Detection
• Cochleagram-based Noise Adapted Speaker Identification System for Distorted Speech