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A Convolutional Neural Network Smartphone App for Real-Time Voice Activity Detection | IEEE Journals & Magazine | IEEE Xplore

A Convolutional Neural Network Smartphone App for Real-Time Voice Activity Detection


This graphical abstract exhibits the developed convolutional neural network architecture for performing voice activity detection in real-time on smartphones.

Abstract:

This paper presents a smartphone app that performs real-time voice activity detection based on convolutional neural network. Real-time implementation issues are discussed...Show More

Abstract:

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.
This graphical abstract exhibits the developed convolutional neural network architecture for performing voice activity detection in real-time on smartphones.
Published in: IEEE Access ( Volume: 6)
Page(s): 9017 - 9026
Date of Publication: 01 February 2018
Electronic ISSN: 2169-3536
PubMed ID: 30250774

Funding Agency:


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