Measurements to determine the ranking accuracy of perceptual models

Linear regression is commonly used in the audio industry to create objective measurement models that predict subjective data. For any model development, the measure used to evaluate the accuracy of the prediction is important. The most common measures assume a linear relationship between the subjective data and the prediction, though in the early stages of model development this is not always the case. Measures based on rank ordering (such as Spearman’s test), can alternatively be used. Spearman’s test, however, does not consider the variance of the subjective data. This paper presents a method of incorporating the subjective variance into the Spearman’s rank ordering test using Monte Carlo simulations, and shows how this can be beneficial in the development of predictive models.