Anti-noise sound recognition based on energy-frequency feature

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 com-bining 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 below 10 dB.