Results on Automated Tuning of a Voice Quality Enhancement System Using Objective Quality Measures
In this work we present a formal procedure for automating the tuning of the various parameters comprising a voice quality enhancer. First, we formalize the problem of tuning as a large-scale nonlinear programming problem. Second, we evaluate the performance of perceptual objective quality measures as optimization criteria for our tuning problem. We then perform a subjective quality assessment to compare the output of a voice enhancer obtained with parameters calculated with these different criteria and also with those obtained through a conventional approach of tuning by expert listening. The results show that using this automated methodology performs well in finding reasonable solutions for the tuning problem, potentially saving time and resources over manual evaluation and tuning.
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