This paper presents Distributed Diffusion Expectation Conditional Maximization Either (DDECME) estimator for Gaussian mixture over wireless sensor network. The main novelty of DDECME estimator with respect to the existed schemes resides in the fact that the propagation of information across the network consumes less time to be embedded in the iterative updating of the parameters, where DDECME estimator adopts the conditional maximized incomplete-data likelihood function to replace the M-steps of DDEM estimator. Numerical examples show that the proposed algorithm practically consumes less time to attain lower NMSE and BER while each node maintains the estimated performance and compares favorably with other estimators.