One approach to improving sound quality is to create a preference map on the basis of several acoustic parameters relevant to auditory perception. The map is derived from several stages of subjective testing, acoustic analysis, and auditory modeling. The multidimensional scaling technique CLASCAL reveals common perceptual dimensions shared by sets of sounds samples, perceptual features specific to each sound, and the different subject classes among listeners. The listeners' are asked to judge the degree of dissimilarity of all pairs of sounds on a continuous scale. The analysis gives a perceptual spatial representation of the sounds. From this analysis, acoustic and auditory modelling analyses can be performed to determine the stimulus parameters that are strongly correlated with different perceptual dimensions and, where possible, with the specific features. The next stage in the analysis involves determining the probability of one sound being preferred to another. An analysis of the data allows a projection of the structure of listeners' preferences onto the physical parameter space underlying the previously determined multidimensional perceptual space. In many cases, it is found that the physical parameters having the most effect on the listeners' preferences are dependent on the set of stimuli being compared. Furthermore, when one stimulus parameter is kept constant across trials, this may altered the effects of other parameters on the listeners' preferences. Therefore context effects must be taken into account in multidimensional sound quality analysis, particularly since the qualitative aspects of most sounds are clearly multidimensional.