A Convolutional Neural Network Smartphone App for Real-Time Voice Activity Detection.
A Convolutional Neural Network Smartphone App for Real-Time Voice Activity Detection.
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DOI：
10.1109/access.2018.2800728
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发表时间：
2018
期刊：
影响因子：
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通讯作者：
Kehtarnavaz N
中科院分区：
文献类型：
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作者：
Sehgal A;Kehtarnavaz N
本文介绍了一种基于卷积神经网络执行实时语音活动检测的智能手机应用程序。讨论了实时实现问题，展示了如何解决与卷积神经网络相关的缓慢推理时间。开发的智能手机应用程序旨在充当听力设备信号处理管道中降噪的开关，使噪声估计或分类能够在嘈杂语音信号的仅噪声部分中进行。将开发的智能手机应用程序与先前开发的语音活动检测应用程序以及两种高度引用的语音活动检测算法进行比较。实验结果表明，使用卷积神经网络开发的应用程序优于以前开发的智能手机应用程序。
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.