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In this study, we investigate the feasibility of utilizing state-of-the-artimage perceptual metrics for evaluating audio signals by representing them asspectrograms. The encouraging outcome of the proposed approach is based on thesimilarity between the neural mechanisms in the auditory and visual pathways.Furthermore, we customise one of the metrics which has a psychoacousticallyplausible architecture to account for the peculiarities of sound signals. Weevaluate the effectiveness of our proposed metric and several baseline metricsusing a music dataset, with promising results in terms of the correlationbetween the metrics and the perceived quality of audio as rated by humanevaluators.

What You Hear Is What You See: Audio Quality Metrics From Image Quality Metrics