The invention provides a speech separation method based on a fuzzy membership function, and belongs to speech separation methods. The fuzzy membership function is combined in the speech separation method, so that more accurate definition of a membership degree of speech time frequency units to a target signal is obtained. An auditory oscillation model is built through human ear auditory system simulation, and speech pitch characteristics are extracted. The speech time frequency units are marked according to pitch cycle characteristics to form foreground streams and background streams. Whether the corresponding time frequency units are targets or noise is judged according to different marks. In the synthesis stage, a target unit multiplies a high weight, a noise unit multiplies a low weight, and resynthetized speech is obtained. By means of the speech separation method, the pitch cycle can be estimated more precisely, the time frequency units can be marked more accurately on the basis of characteristic clues, and the more complete target speech can be obtained. Due to the fact that the method is based on the pitch characteristics of the speech, good separation effects in complex and non-stationary noise are achieved, and the application range is wide.