Sound source identification by neural networks

Cristian Gabriel  Carangui Velecela; Diego Paul Chacon Troya

doi:10.1109/INES.2016.7555117

Sound source identification by neural networks

Cristian Gabriel Carangui Velecela
, Diego Paul Chacon Troya

Grupo de Investigación en Energías (GIE)

Research output: Conference contribution › peer-review

Abstract

Sound source identification is an intrinsic process that helps people to interact with the environment around them, allowing to interpret the information transmitted by humans, animals and machines, for this reason, it is mimicked by different types of autonomous machines. This article presents the development and implementation of a new method to identify the origin of the sound source for a small robotic system based on three microphones, using two types of artificial neural network, the first one-ADALINE structure, used to obtain a noise environmental filter and the second one-BACKPROPAGATION's structure to identify the source sound in a range between 0 and 180 degrees employing. The identification based on differents tests permit us to have an error of 7% in the last stage. The present project was developed with NI MyRIO device and the software LabVIEW and Matlab.

Original language	English
Title of host publication	INES 2016 - 20th Jubilee IEEE International Conference on Intelligent Engineering Systems, Proceedings
Editors	Aniko Szakal
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	183-188
Number of pages	6
ISBN (Electronic)	9781509012169
DOIs	https://doi.org/10.1109/INES.2016.7555117
Publication status	Published - 26 Aug 2016
Event	20th Jubilee IEEE International Conference on Intelligent Engineering Systems, INES 2016 - Budapest, Hungary Duration: 30 Jun 2016 → 2 Jul 2016

Publication series

Name	INES 2016 - 20th Jubilee IEEE International Conference on Intelligent Engineering Systems, Proceedings

Conference

Conference	20th Jubilee IEEE International Conference on Intelligent Engineering Systems, INES 2016
Country/Territory	Hungary
City	Budapest
Period	30/06/16 → 2/07/16

Bibliographical note

Publisher Copyright:
© 2016 IEEE.

Areas de Conocimiento del CACES

317A Electricidad y energía

Access to Document

10.1109/INES.2016.7555117

Cite this

Carangui Velecela, C. G., & Troya, D. P. C. (2016). Sound source identification by neural networks. In A. Szakal (Ed.), INES 2016 - 20th Jubilee IEEE International Conference on Intelligent Engineering Systems, Proceedings (pp. 183-188). Article 7555117 (INES 2016 - 20th Jubilee IEEE International Conference on Intelligent Engineering Systems, Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/INES.2016.7555117

Carangui Velecela, Cristian Gabriel ; Troya, Diego Paul Chacon. / Sound source identification by neural networks. INES 2016 - 20th Jubilee IEEE International Conference on Intelligent Engineering Systems, Proceedings. editor / Aniko Szakal. Institute of Electrical and Electronics Engineers Inc., 2016. pp. 183-188 (INES 2016 - 20th Jubilee IEEE International Conference on Intelligent Engineering Systems, Proceedings).

@inproceedings{ff230efef90146ecbe01758ee6c862fc,

title = "Sound source identification by neural networks",

abstract = "Sound source identification is an intrinsic process that helps people to interact with the environment around them, allowing to interpret the information transmitted by humans, animals and machines, for this reason, it is mimicked by different types of autonomous machines. This article presents the development and implementation of a new method to identify the origin of the sound source for a small robotic system based on three microphones, using two types of artificial neural network, the first one-ADALINE structure, used to obtain a noise environmental filter and the second one-BACKPROPAGATION's structure to identify the source sound in a range between 0 and 180 degrees employing. The identification based on differents tests permit us to have an error of 7\% in the last stage. The present project was developed with NI MyRIO device and the software LabVIEW and Matlab.",

keywords = "ADALINE, adaptive filter, BACKPROPAGATION, neural network, Sound source identification",

author = "\{Carangui Velecela\}, \{Cristian Gabriel\} and Troya, \{Diego Paul Chacon\}",

note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; 20th Jubilee IEEE International Conference on Intelligent Engineering Systems, INES 2016 ; Conference date: 30-06-2016 Through 02-07-2016",

year = "2016",

month = aug,

day = "26",

doi = "10.1109/INES.2016.7555117",

language = "English",

series = "INES 2016 - 20th Jubilee IEEE International Conference on Intelligent Engineering Systems, Proceedings",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "183--188",

editor = "Aniko Szakal",

booktitle = "INES 2016 - 20th Jubilee IEEE International Conference on Intelligent Engineering Systems, Proceedings",

address = "United States",

}

Carangui Velecela, CG & Troya, DPC 2016, Sound source identification by neural networks. in A Szakal (ed.), INES 2016 - 20th Jubilee IEEE International Conference on Intelligent Engineering Systems, Proceedings., 7555117, INES 2016 - 20th Jubilee IEEE International Conference on Intelligent Engineering Systems, Proceedings, Institute of Electrical and Electronics Engineers Inc., pp. 183-188, 20th Jubilee IEEE International Conference on Intelligent Engineering Systems, INES 2016, Budapest, Hungary, 30/06/16. https://doi.org/10.1109/INES.2016.7555117

Sound source identification by neural networks. / Carangui Velecela, Cristian Gabriel ; Troya, Diego Paul Chacon.
INES 2016 - 20th Jubilee IEEE International Conference on Intelligent Engineering Systems, Proceedings. ed. / Aniko Szakal. Institute of Electrical and Electronics Engineers Inc., 2016. p. 183-188 7555117 (INES 2016 - 20th Jubilee IEEE International Conference on Intelligent Engineering Systems, Proceedings).

Research output: Conference contribution › peer-review

TY - GEN

T1 - Sound source identification by neural networks

AU - Carangui Velecela, Cristian Gabriel

AU - Troya, Diego Paul Chacon

PY - 2016/8/26

Y1 - 2016/8/26

N2 - Sound source identification is an intrinsic process that helps people to interact with the environment around them, allowing to interpret the information transmitted by humans, animals and machines, for this reason, it is mimicked by different types of autonomous machines. This article presents the development and implementation of a new method to identify the origin of the sound source for a small robotic system based on three microphones, using two types of artificial neural network, the first one-ADALINE structure, used to obtain a noise environmental filter and the second one-BACKPROPAGATION's structure to identify the source sound in a range between 0 and 180 degrees employing. The identification based on differents tests permit us to have an error of 7% in the last stage. The present project was developed with NI MyRIO device and the software LabVIEW and Matlab.

AB - Sound source identification is an intrinsic process that helps people to interact with the environment around them, allowing to interpret the information transmitted by humans, animals and machines, for this reason, it is mimicked by different types of autonomous machines. This article presents the development and implementation of a new method to identify the origin of the sound source for a small robotic system based on three microphones, using two types of artificial neural network, the first one-ADALINE structure, used to obtain a noise environmental filter and the second one-BACKPROPAGATION's structure to identify the source sound in a range between 0 and 180 degrees employing. The identification based on differents tests permit us to have an error of 7% in the last stage. The present project was developed with NI MyRIO device and the software LabVIEW and Matlab.

KW - ADALINE

KW - adaptive filter

KW - BACKPROPAGATION

KW - neural network

KW - Sound source identification

UR - https://www.scopus.com/pages/publications/84987934996

U2 - 10.1109/INES.2016.7555117

DO - 10.1109/INES.2016.7555117

M3 - Conference contribution

AN - SCOPUS:84987934996

T3 - INES 2016 - 20th Jubilee IEEE International Conference on Intelligent Engineering Systems, Proceedings

SP - 183

EP - 188

BT - INES 2016 - 20th Jubilee IEEE International Conference on Intelligent Engineering Systems, Proceedings

A2 - Szakal, Aniko

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 20th Jubilee IEEE International Conference on Intelligent Engineering Systems, INES 2016

Y2 - 30 June 2016 through 2 July 2016

ER -

Carangui Velecela CG, Troya DPC. Sound source identification by neural networks. In Szakal A, editor, INES 2016 - 20th Jubilee IEEE International Conference on Intelligent Engineering Systems, Proceedings. Institute of Electrical and Electronics Engineers Inc. 2016. p. 183-188. 7555117. (INES 2016 - 20th Jubilee IEEE International Conference on Intelligent Engineering Systems, Proceedings). doi: 10.1109/INES.2016.7555117

Sound source identification by neural networks

Abstract

Publication series

Conference

Bibliographical note

Areas de Conocimiento del CACES

Access to Document

Other files and links

Cite this