  Objective measurement of perceptually motivated music attributes has
application in both target driven mixing and mastering methodologies and music
information retrieval. This work proposes a perceptual model of mix clarity
which decomposes a mixed input signal into transient, steady-state, and
residual components. Masking thresholds are calculated for each component and
their relative relationship is used to determine an overall masking score as
the model's output. Three variants of the model were tested against subjective
mix clarity scores gathered from a controlled listening test. The best
performing variant achieved a Spearman's rank correlation of rho = 0.8382
(p<0.01). Furthermore, the model output was analysed using an independent
dataset generated by progressively applying degradation effects to the test
stimuli. Analysis of the model suggested a close relationship between the
proposed model and the subjective mix clarity scores particularly when masking
was measured using linearly spaced analysis bands. Moreover, the presence of
noise-like residual signals was shown to have a negative effect on the
perceived mix clarity.
