Spoken Speech Enhancement using EEG

SPOKEN SPEECH ENHANCEMENT USING EEG Gautam Krishna null Y an Han null Co Tran Mason Carnahan Ahmed H T ewfik Brain Machine Interface Lab, The University of Texas at Austin ABSTRACT In this paper we demonstrate spoken speech enhancement using electroencephalography (EEG) signals using a generative adversarial network (GAN) based model and Long short-term Memory (LSTM) regression based model. Our results demonstrate that EEG features can be used to clean speech recorded in presence of background noise. Index T erms -- electroencephalograpgy (EEG), speech enhancement, deep learning 1. INTRODUCTION Speech enhancement is the process of improving the quality of speech whose quality was degraded due to additive noise. Speech enhancement is a critical preprocessing method used to improve the performance of automatic speech recognition (ASR) systems operating in presence of background noise. Noisy speech is first fed into a speech enhancement system to produce enhanced speech which is then fed into the ASR model.