  In this paper, we propose a novel information theoretic model to interpret
the entire "transmission chain" comprising stimulus generation, brain
processing by the human subject, and the electroencephalograph (EEG) response
measurements as a nonlinear, time-varying communication channel with memory. We
use mutual information (MI) as a measure to assess audio quality perception by
directly measuring the brainwave responses of the human subjects using a high
resolution EEG. Our focus here is on audio where the quality is impaired by
time varying distortions. In particular, we conduct experiments where subjects
are presented with audio whose quality varies with time between different
possible quality levels. The recorded EEG measurements can be modeled as a
multidimensional Gaussian mixture model (GMM). In order to make the computation
of the MI feasible, we present a novel low-complexity approximation technique
for the differential entropy of the multidimensional GMM. We find the proposed
information theoretic approach to be successful in quantifying subjective audio
quality perception, with the results being consistent across different music
sequences and distortion types.
