Environmental sounds recognition system using the speech recognition system techniques

被引：5

作者：

Uribe, OA ^{[1
]}

Meana, HMP ^{[1
]}

Miyatake, MN ^{[1
]}

机构：

[1] IPN, Sect Postgrad & Invest Studies, ESIME, Mexico City 07738, DF, Mexico

来源：

2005 2nd International Conference on Electrical & Electronics Engineering (ICEEE) | 2005年

关键词：

artificial neural network; LPC-Cepstral; Fourier transform;

D O I：

10.1109/ICEEE.2005.1529562

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

This paper proposes an environmental sounds recognition system using LPC-Cepstral coefficients for characterization and a backpropagation artificial neural network as verification method. LPC-Cepstral data are totally dependent on the sound-source from which they are computed. This system is evaluated using a database containing files of four different sound-sources under a variety of recording conditions. Two neural networks are trained with the magnitude of the discrete Fourier transform of the LPC-Cepstral matrices. The global percentage of verification was of 96.66%. The percentage of verification can be improved if the number of feature vectors (coefficients) is incremented in the neural network-training phase. Basically the idea here is to apply the techniques founded in speech recognition systems to an environmental sounds recognition system.

引用

页码：13 / 16

页数：4