Segmental preclassification for improved objective speech quality measures

This paper presents some results of an experimental study of the use of segmental preclassification as a technique for improving the performance of objective speech quality measures. In all such measures tested, the distorted speech was first divided into segments, and each segment was classified by an objective classification procedure into one of four classes: "silence," "fricative," "vocalic," and "nasal." Separate objective measures were then computed for each class, and a final overall objective quality measure was computed as a weighted sum of the individual classified measures. Figures-of-merit for the objective measures tested were computed using correlation analysis between a data base of objective quality measures computed using the classified measures and subjective speech quality measures across the same set of distorted and coded speech data. The subjective quality test which was used was the DAM test.