1. A single-ended speech quality measurement method comprising the steps of: for each frame of a plurality of frames containing a speech signal that has been processed by network equipment, transmitted on a communications link, or both: extracting perceptual features; and classifying the frame based on the perceptual features into a class selected from a set of classes including voiced and unvoiced; and for the frames of each class: assessing the perceptual features with a statistical model of that class to generate an indicator of speech quality, the statistical model of that class being part of a reference model which includes at least one statistical model for each class of the set of classes, the reference model generated prior to extracting the perceptual features to form indicators of speech quality, including assessing at least some unvoiced frames; and employing the indicators of speech quality from different classes to produce an estimate of subjective speech quality score without reference to a corresponding speech signal that has not been processed by network equipment, transmitted on a communications link, or both.
2. The method of claim 1 including the further step of separately modeling a probability distribution of the features for each frame class and different classes of speech signals with statistical models.