Voice Activity Detection in presence of background noise using EEG

11/08/2019
by   Gautam Krishna, et al.
0

In this paper we demonstrate that performance of voice activity detection (VAD) system operating in presence of background noise can be improved by concatenating acoustic input features with electroencephalography (EEG) features. We also demonstrate that VAD using only EEG features shows better performance than VAD using only acoustic features in presence of background noise. We implemented a recurrent neural network (RNN) based VAD system and we demonstrate our results for two different data sets recorded in presence of different noise conditions in this paper.

READ FULL TEXT
research
03/07/2020

Speaker Identification using EEG

In this paper we explore speaker identification using electroencephalogr...
research
01/12/2021

Practical Speech Re-use Prevention in Voice-driven Services

Voice-driven services (VDS) are being used in a variety of applications ...
research
05/28/2019

Automatic Quality Control and Enhancement for Voice-Based Remote Parkinson's Disease Detection

The performance of voice-based Parkinson's disease (PD) detection system...
research
01/31/2022

Jet noise characterization for advanced pipeline leak detection

The detection of leaks in pipeline transportation systems is a matter of...
research
03/07/2019

Voice Activity Detection: Merging Source and Filter-based Information

Voice Activity Detection (VAD) refers to the problem of distinguishing s...
research
08/12/2021

Deep Neural Network Voice Activity Detector for Downsampled Audio Data: An Experiment Report

Sociometric badges are an emerging technology for study how teams intera...
research
03/11/2019

Labeler-hot Detection of EEG Epileptic Transients

Preventing early progression of epilepsy and so the severity of seizures...

Please sign up or login with your details

Forgot password? Click here to reset