Sound source identification by neural networks

Cristian Gabriel Carangui Velecela, Diego Paul Chacon Troya

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-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 languageEnglish
Title of host publicationINES 2016 - 20th Jubilee IEEE International Conference on Intelligent Engineering Systems, Proceedings
EditorsAniko Szakal
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages183-188
Number of pages6
ISBN (Electronic)9781509012169
DOIs
StatePublished - 26 Aug 2016
Event20th Jubilee IEEE International Conference on Intelligent Engineering Systems, INES 2016 - Budapest, Hungary
Duration: 30 Jun 20162 Jul 2016

Publication series

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

Conference

Conference20th Jubilee IEEE International Conference on Intelligent Engineering Systems, INES 2016
Country/TerritoryHungary
CityBudapest
Period30/06/162/07/16

Bibliographical note

Publisher Copyright:
© 2016 IEEE.

Keywords

  • ADALINE
  • adaptive filter
  • BACKPROPAGATION
  • neural network
  • Sound source identification

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