Anti-noise sound recognition based on energy-frequency feature
Zhou, Xiaomin, Li, Ying
tlooto Summary
The experimental results show that the proposed new technology of animal sound recognition based on energy-frequency( E-F) feature can achieve better recognition effect even when the SNR is below10 dB.
Abstract
In the natural environment,non-stationary background noise affects the animal sound recognition directly. Given this problem,a new technology of animal sound recognition based on energy-frequency( E-F) feature is proposed in this paper. The animal sound is turned into spectrogram to show the energy,time and frequency characteristics. The sub-band frequency division and sub-band energy division are carried out on the spectrogram for extracting the statistical characteristic of energy and frequency,so as to achieve sub-band power distribution( SPD) and sub-band division. Radon transform( RT) and discrete wavelet transform( DWT) are employed to obtain the important projection coefficients,and the energy values of sub-band frequencies are calculated to extract the sub-band frequency feature. The E-F feature is formed by combining the SPD feature and sub-band energy value feature. The classification is achieved by support vector machine( SVM)classifier. The experimental results show that the method can achieve better recognition effect even when the SNR is below10 dB.
Citation format
ZHOU, et al. Anti-noise sound recognition based on energy-frequency feature. CAAI Transactions on Intelligent Systems, 2015, 10: 810–819.