In this paper, we propose a speech enhancement algorithm by using MAP estimation with variable speech spectral amplitude probability density function (speech PDF). The variable speech PDF has two adaptive shape parameters which affect the quality of enhanced speech. Noise can be efficiently suppressed when these parameters are properly applied so that the variable speech PDF shape fits to the real-speech PDF one. We derive adaptive shape parameters from real-speech PDF in various narrow SNR intervals. The proposed speech enhancement algorithm with adaptive shape parameters is examined and compared to conventional algorithms. The simulation results show that the proposed method improved SegSNR around 6 and 9dB when the input speech signal was corrupted by white and tunnel noises at 0dB, respectively.