Acoustic event detection with two-stage judgement in the noisy environment

Aiming at the problem of inaccurate event location in noisy environment by existing acoustic even detection technology, this paper presents an acoustic event detection algorithm based on two-stage judgement. Firstly, the acoustic events existing in the audio signal are located by the two-stage judgement detection method, both of the distance of the Mel Frequency Cepstral Coefficients (MFCC) and the short-time energy between each audio signal frame and the noise average are calculated, respectively. The MFCC distance in the frequency domain which can produce fine but incomplete results is the first judgement; the energy distance in the time domain is the second judgement, which is used to supplement the first judgment. Studies have shown that the Gammatone filter bank is biologically closer to the human ear structure than the Mel filter bank. The Gammatone Frequency Cepstral Coefficients (GFCC) of the detected acoustic events were then extracted. The detected acoustic events are classified by the Gaussian Mixture Model (GMM). By analyzing the experimental results, the algorithm can solve the problem that the sound feature information is insufficient and the noise segment boundary is not clear. This system is more suitable for the situation where a variety of acoustic events should be analyzed.