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Telecommunications and Radio Engineering
SJR: 0.202 SNIP: 0.2 CiteScore™: 0.23

ISSN Печать: 0040-2508
ISSN Онлайн: 1943-6009

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Telecommunications and Radio Engineering

DOI: 10.1615/TelecomRadEng.v65.i3.80
pages 271-279

Environmental Sounds Recognition

O. Aranda-Uribe
ESIME Culhuacan, National Polytechnic Institute of Mexico, Mexico
Mariko Nakano-Miyatake
National Polytechnic Institute, IPN, Mexico City
Hector Manuel Perez-Meana
National Polytechnic Institute of Mexico

Краткое описание

This paper describes an environmental sounds recognition system using LPC-Cepstral coefficients as feature vectors and an artificial neural network backpropagation as recognition method. LPC-Cepstral data are totally dependents of the sound-source from which are computed. This system is evaluated using a database containing files from four different sound-sources under a variety of recording conditions. The training patterns used in the network-training ad testing processes, are extracted from the Discrete Fourier transform magnitude of the LPC-Cepstral matrices. The global percentages of classification obtained in the network-testing process are 98.2% and 96.8%. Basically the idea here is to apply the techniques found in speech recognition systems to an environmental sounds recognition system.

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