Design of Sound Recognition System Based on Modified Neural Network

Su Xiang Qian; Fu Xi Liu; Jian Cao

doi:10.4028/www.scientific.net/AMM.278-280.1178

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 278-280Design of Sound Recognition System Based on...

Design of Sound Recognition System Based on Modified Neural Network

Abstract:

Sound recognition based on neural network is a technique that can put a resolution to exceeding artificial identification. Three kinds of neural network recognition models, adopting MFCC and difference MFCC, are discussed. According to six kinds of typical gunshots we design a kind of sound recognition system based on BP neural network optimized by PSO that uses MFCC and difference MFCC as a characteristic quantity to recognize sound signal. In the experiment PSO is used to optimize the network’s initial weights and threshold value. The experiment’s results show that BP neural network optimized by PSO using both MFCC characteristic quantity and difference MFCC characteristic quantity have a relatively lower error and a relatively faster speed than other ways discussed in the article, and the designed system reaches the expected goal.

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Periodical:

Applied Mechanics and Materials (Volumes 278-280)

Pages:

1178-1181

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.278-280.1178

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Online since:

January 2013

Authors:

Su Xiang Qian, Fu Xi Liu, Jian Cao

Keywords:

BP Neural Network (BPNN), Difference MFCC, MFCC, Particle Swarm Optimization (PSO), Sound Recognition

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