activity
20192021
most citedImproving EEG based Continuous Speech Recognition

10 citations · 23 across the 9 of their papers we have counts for

collaborators

22 papers

cs.SD2021

Brain Signals to Rescue Aphasia, Apraxia and Dysarthria Speech Recognition

Gautam Krishna, Mason Carnahan, Shilpa Shamapant +6

In this paper, we propose a deep learning-based algorithm to improve the performance of automatic speech recognition (ASR) systems for aphasia, apraxia, and dysarthria speech by ut…

eess.AS20201 cited

Speech Recognition using EEG signals recorded using dry electrodes

Gautam Krishna, Co Tran, Mason Carnahan +2

In this paper, we demonstrate speech recognition using electroencephalography (EEG) signals obtained using dry electrodes on a limited English vocabulary consisting of three vowels…

eess.AS20203 cited

Constrained Variational Autoencoder for improving EEG based Speech Recognition Systems

Gautam Krishna, Co Tran, Mason Carnahan +1

In this paper we introduce a recurrent neural network (RNN) based variational autoencoder (VAE) model with a new constrained loss function that can generate more meaningful electro…

eess.AS2020

Predicting Different Acoustic Features from EEG and towards direct synthesis of Audio Waveform from EEG

Gautam Krishna, Co Tran, Mason Carnahan +1

In [1,2] authors provided preliminary results for synthesizing speech from electroencephalography (EEG) features where they first predict acoustic features from EEG features and th…

eess.AS20201 cited

Understanding effect of speech perception in EEG based speech recognition systems

Gautam Krishna, Co Tran, Mason Carnahan +1

The electroencephalography (EEG) signals recorded in parallel with speech are used to perform isolated and continuous speech recognition. During speaking process, one also hears hi…

eess.AS20202 cited

Improving EEG based continuous speech recognition using GAN

Gautam Krishna, Co Tran, Mason Carnahan +1

In this paper we demonstrate that it is possible to generate more meaningful electroencephalography (EEG) features from raw EEG features using generative adversarial networks (GAN)…