Acoustic recognition method in low SNR based on human ear bionics

The long-distance acoustic signal has low energy, high concealment and low signal-to-noise ratio (SNR), thus is often submerged in noise and interference. The conventional method of acoustic detection cannot classify or recognize the target. A sound recognition method has been proposed to simulate human ear auditory process by making the best of sound recognition advantage of human ear. First of all, those parts which function as energy gathering, frequency-selective amplification or information transmission in human ear are selected, and the auditory model of each part is established independently. Then, the structural parameters of each model are extracted, and the influence and change rules of structural parameters on the auditory signal are studied and optimized according to the auditory law. Finally, the auditory model is reconstructed based on the parameters extracted from each component, and the integrated model is used to carry out the voice recognition experiment under low SNR. The recognition rate of low SNR (−5 dB) acoustic event is improved by 6.5%.