A Convolutional Neural Network Smartphone App for Real-Time Voice Activity Detection
This paper presents a smartphone app that performs real-time voice activity detection based on convolutional neural network. Real-time implementation issues are discussed showing how the slow inference time associated with convolutional neural networks is addressed. The developed smartphone app is m...
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doaj-281d3ba55cc746d5b1c77b849196fd6c2021-03-29T20:35:12ZengIEEEIEEE Access2169-35362018-01-0169017902610.1109/ACCESS.2018.28007288278160A Convolutional Neural Network Smartphone App for Real-Time Voice Activity DetectionAbhishek Sehgal0https://orcid.org/0000-0001-7128-6438Nasser Kehtarnavaz1Department of Electrical and Computer Engineering, University of Texas at Dallas, Richardson, TX, USADepartment of Electrical and Computer Engineering, University of Texas at Dallas, Richardson, TX, USAThis paper presents a smartphone app that performs real-time voice activity detection based on convolutional neural network. Real-time implementation issues are discussed showing how the slow inference time associated with convolutional neural networks is addressed. The developed smartphone app is meant to act as a switch for noise reduction in the signal processing pipelines of hearing devices, enabling noise estimation or classification to be conducted in noise-only parts of noisy speech signals. The developed smartphone app is compared with a previously developed voice activity detection app as well as with two highly cited voice activity detection algorithms. The experimental results indicate that the developed app using convolutional neural network outperforms the previously developed smartphone app.https://ieeexplore.ieee.org/document/8278160/Smartphone app for real-time voice activity detectionconvolutional neural network voice activity detectorreal-time implementation of convolutional neural network |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Abhishek Sehgal Nasser Kehtarnavaz |
spellingShingle |
Abhishek Sehgal Nasser Kehtarnavaz A Convolutional Neural Network Smartphone App for Real-Time Voice Activity Detection IEEE Access Smartphone app for real-time voice activity detection convolutional neural network voice activity detector real-time implementation of convolutional neural network |
author_facet |
Abhishek Sehgal Nasser Kehtarnavaz |
author_sort |
Abhishek Sehgal |
title |
A Convolutional Neural Network Smartphone App for Real-Time Voice Activity Detection |
title_short |
A Convolutional Neural Network Smartphone App for Real-Time Voice Activity Detection |
title_full |
A Convolutional Neural Network Smartphone App for Real-Time Voice Activity Detection |
title_fullStr |
A Convolutional Neural Network Smartphone App for Real-Time Voice Activity Detection |
title_full_unstemmed |
A Convolutional Neural Network Smartphone App for Real-Time Voice Activity Detection |
title_sort |
convolutional neural network smartphone app for real-time voice activity detection |
publisher |
IEEE |
series |
IEEE Access |
issn |
2169-3536 |
publishDate |
2018-01-01 |
description |
This paper presents a smartphone app that performs real-time voice activity detection based on convolutional neural network. Real-time implementation issues are discussed showing how the slow inference time associated with convolutional neural networks is addressed. The developed smartphone app is meant to act as a switch for noise reduction in the signal processing pipelines of hearing devices, enabling noise estimation or classification to be conducted in noise-only parts of noisy speech signals. The developed smartphone app is compared with a previously developed voice activity detection app as well as with two highly cited voice activity detection algorithms. The experimental results indicate that the developed app using convolutional neural network outperforms the previously developed smartphone app. |
topic |
Smartphone app for real-time voice activity detection convolutional neural network voice activity detector real-time implementation of convolutional neural network |
url |
https://ieeexplore.ieee.org/document/8278160/ |
work_keys_str_mv |
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_version_ |
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