Non-intrusive GMM-based speech quality measurement

We propose a non-intrusive speech quality measurement algorithm based on using Gaussian-mixture probability models of features of undegraded speech signals as an artificial reference model of "clean" speech behaviour. The consistency between the features of the test speech signal and the reference model serves as an indicator of speech quality. Consistency measures are calculated and mapped to an objective speech quality score using a multivariate adaptive regression splines function. Simulation results show that the proposed method offers accurate and yet low-complexity measurement of speech quality.