Sound monitoring method based on wavelets and sparse representation classifier

Sound is only the important way of human perception on the world, but also reflects some important characteristics of human behaviors under certain circumstances. This paper mainly presents the sound event recognition method using Mel-frequency Morlet wavelet subband (MFMWS) feature and sparse representation-based classifier (SRC) aiming at security monitoring applications. In order to evaluate its performance, the experiments on sound event recognition were designed and implemented. The experimental results show that the proposed method possesses better overall classification accuracy than the baseline schemes.