Simulation of Human Ear Recognition Sound Direction Based on Convolutional Neural Network

In recent years, more and more people are applying Convolutional Neural Networks to the study of sound signals. The main reason is the translational invariance of convolution in time and space. Thereby the diversity of the sound signal can be overcome. However, in terms of sound direction recognitio...

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Autores principales:	Wang Zhuhe, Li Nan, Wu Tao, Zhang Haoxuan, Feng Tao
Formato:	article
Lenguaje:	EN
Publicado:	De Gruyter 2020
Materias:	convolutional neural network simulated human head dual-channel raw data gcc probability distributions Science Q Electronic computers. Computer science QA75.5-76.95
Acceso en línea:	https://doaj.org/article/f31548cf575547efbec9a13fa73d2164
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id	oai:doaj.org-article:f31548cf575547efbec9a13fa73d2164
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spelling	oai:doaj.org-article:f31548cf575547efbec9a13fa73d21642021-12-05T14:10:51ZSimulation of Human Ear Recognition Sound Direction Based on Convolutional Neural Network2191-026X10.1515/jisys-2019-0250https://doaj.org/article/f31548cf575547efbec9a13fa73d21642020-07-01T00:00:00Zhttps://doi.org/10.1515/jisys-2019-0250https://doaj.org/toc/2191-026XIn recent years, more and more people are applying Convolutional Neural Networks to the study of sound signals. The main reason is the translational invariance of convolution in time and space. Thereby the diversity of the sound signal can be overcome. However, in terms of sound direction recognition, there are also problems such as a microphone matrix being too large, and feature selection. This paper proposes a sound direction recognition using a simulated human head with microphones at both ears. Theoretically, the two microphones cannot distinguish the front and rear directions. However, we use the original data of the two channels as the input of the convolutional neural network, and the resolution effect can reach more than 0.9. For comparison, we also chose the delay feature (GCC) for sound direction recognition. Finally, we also conducted experiments that used probability distributions to identify more directions.Wang ZhuheLi NanWu TaoZhang HaoxuanFeng TaoDe Gruyterarticleconvolutional neural networksimulated human headdual-channel raw datagccprobability distributionsScienceQElectronic computers. Computer scienceQA75.5-76.95ENJournal of Intelligent Systems, Vol 30, Iss 1, Pp 209-223 (2020)
institution	DOAJ
collection	DOAJ
language	EN
topic	convolutional neural network simulated human head dual-channel raw data gcc probability distributions Science Q Electronic computers. Computer science QA75.5-76.95
spellingShingle	convolutional neural network simulated human head dual-channel raw data gcc probability distributions Science Q Electronic computers. Computer science QA75.5-76.95 Wang Zhuhe Li Nan Wu Tao Zhang Haoxuan Feng Tao Simulation of Human Ear Recognition Sound Direction Based on Convolutional Neural Network
description	In recent years, more and more people are applying Convolutional Neural Networks to the study of sound signals. The main reason is the translational invariance of convolution in time and space. Thereby the diversity of the sound signal can be overcome. However, in terms of sound direction recognition, there are also problems such as a microphone matrix being too large, and feature selection. This paper proposes a sound direction recognition using a simulated human head with microphones at both ears. Theoretically, the two microphones cannot distinguish the front and rear directions. However, we use the original data of the two channels as the input of the convolutional neural network, and the resolution effect can reach more than 0.9. For comparison, we also chose the delay feature (GCC) for sound direction recognition. Finally, we also conducted experiments that used probability distributions to identify more directions.
format	article
author	Wang Zhuhe Li Nan Wu Tao Zhang Haoxuan Feng Tao
author_facet	Wang Zhuhe Li Nan Wu Tao Zhang Haoxuan Feng Tao
author_sort	Wang Zhuhe
title	Simulation of Human Ear Recognition Sound Direction Based on Convolutional Neural Network
title_short	Simulation of Human Ear Recognition Sound Direction Based on Convolutional Neural Network
title_full	Simulation of Human Ear Recognition Sound Direction Based on Convolutional Neural Network
title_fullStr	Simulation of Human Ear Recognition Sound Direction Based on Convolutional Neural Network
title_full_unstemmed	Simulation of Human Ear Recognition Sound Direction Based on Convolutional Neural Network
title_sort	simulation of human ear recognition sound direction based on convolutional neural network
publisher	De Gruyter
publishDate	2020
url	https://doaj.org/article/f31548cf575547efbec9a13fa73d2164
work_keys_str_mv	AT wangzhuhe simulationofhumanearrecognitionsounddirectionbasedonconvolutionalneuralnetwork AT linan simulationofhumanearrecognitionsounddirectionbasedonconvolutionalneuralnetwork AT wutao simulationofhumanearrecognitionsounddirectionbasedonconvolutionalneuralnetwork AT zhanghaoxuan simulationofhumanearrecognitionsounddirectionbasedonconvolutionalneuralnetwork AT fengtao simulationofhumanearrecognitionsounddirectionbasedonconvolutionalneuralnetwork
_version_	1718371656078983168

Simulation of Human Ear Recognition Sound Direction Based on Convolutional Neural Network

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