학술논문
Speaker-Independent Brain Enhanced Speech Denoising
Document Type
Conference
Author
Source
ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) Acoustics, Speech and Signal Processing (ICASSP), ICASSP 2021 - 2021 IEEE International Conference on. :1310-1314 Jun, 2021
Subject
Language
ISSN
2379-190X
Abstract
The auditory system is extremely efficient in extracting attended auditory information in the presence of competing speakers. Single-channel speech enhancement algorithms, however, greatly lack this efficacy. In this paper, we propose a novel deep learning method referred to as the Brain Enhanced Speech Denoiser (BESD), that takes advantage of the attended auditory information present in the brain activity of the listener to denoise a multi-talker speech. We use this information to modulate the features learned from the sound and the brain activity, in order to perform speech enhancement. We show that our method successfully enhances a speech mixture, without prior information about the attended speaker, using electroencephalography (EEG) signals recorded from the listener. This makes it a great candidate for realistic applications where no prior information about the attended speaker is available, such as hearing aids or cell phones.