Abstract: The observation of speech spectral structure shows that the statistics of speech signal cannot be well determined by a simple probability density function. Therefore, this paper presents a speech enhancement algorithm based on super-Gaussian mixture model. Firstly, the super Gaussian mixture model is employed to model the speech spectral amplitude, which is more flexible in capturing the statistical behavior of speech signals than the conventional simple speech model. Where after, the PDF and weight of the mixture component are further adapted, which can overcome the disadvantage that the traditional simple speech model cannot well track the dynamic characteristics of the speech signal. The simulation results show that the proposed algorithm achieves better noise suppression and lower speech distortion compared to the conventional short-time spectral estimation algorithms.