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2014•Journal of Projectiles.Rockets.Missiles and GuidanceRequires access

Application of Biomimetic Technology to Feature Extraction from Acoustic Objects

Sun Yuejua

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Abstract

In view of principle of biomimetic technology,feature extraction from acoustic targets can influence the performance of whole system to enhance recognition performance. Several kinds of time domain,frequency domain and cepstrum domain were researched,including linear prediction cepstrum coefficient,mel-frequency cepstrum coefficient( MFCC),dynamic acoustic feature and wavelet feature and etc. The recognition results of components of different feature for acoustic target system were given. The results show that recognition rate based on MFCC is higher than others reaching 96. 8% under different object.

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What this paper is about

In view of principle of biomimetic technology,feature extraction from acoustic targets can influence the performance of whole system to enhance recognition performance. Several kinds of time domain,frequency domain and cepstrum domain were researched,including linear prediction cepstrum coefficient,mel-frequency cepstrum coefficient( MFCC),dynamic acoustic feature and wavelet feature and etc. The recognition results of components of different feature for acoustic target system were given. The results show that recognition rate based on MFCC is higher than others reaching 96. 8% under different object.

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Available abstract

In view of principle of biomimetic technology,feature extraction from acoustic targets can influence the performance of whole system to enhance recognition performance. Several kinds of time domain,frequency domain and cepstrum domain were researched,including linear prediction cepstrum coefficient,mel-frequency cepstrum coefficient( MFCC),dynamic acoustic feature and wavelet feature and etc. The recognition results of components of different feature for acoustic target system were given. The results show that recognition rate based on MFCC is higher than others reaching 96. 8% under different object.

Key concepts: Mel-frequency cepstrum, Cepstrum, Feature extraction, Feature (linguistics), Frequency domain, Computer science, Pattern recognition (psychology), Speech recognition

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