We propose a generalized positive-definite and skew-Hermitian splitting method to solve the large sparse saddle point problems based on the positive-definite splitting. The method first uses the positive-definite splitting of matrix to construct two splitting forms of the saddle-point matrix. Then, the two splitting formats are used to construct the GPSS iteration. Thirdly, the necessary and sufficient conditions for the iteration convergence are given. Finally, some numerical comparison experiments are carried out and the results show that the GPSS is more effective than "the positive-definite and skew-Hermitian splitting" (PSS) method and "the Hermitian and skew-Hermitian splitting" (HSS) method.