Algorithms for Assessing the Subjectivity of Perceptually Weighted Audible Errors
Auditory modeling is used increasingly to provide an objective prediction of the subjective performance of audio systems. Such techniques typically compare the predicted auditory stimulation of original and processed audio signals to produce an estimate of audible error that can be presented as an error surface. The use of audible error surfaces as a diagnostic tool is investigated and an algorithmic interpretation provided to predict subjective opinion. The applicability of the technique across a range of industries is discussed.
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