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Subjective Effects of Regularization on Inverse Filtering
Previous work has shown that inverse filtering to correct the impulse response (IR) of an audio system can degrade the subjective quality in certain conditions. The severity of the degradation depends on both the response of the system that is being inverted and filter inversion method used to correct this response. Regularization has been proposed as a means to improve the performance of inverse filtering by limiting how much 'work' the inverse filter will do to correct the system response. In this paper, formal subjective tests were conducted to examine the subjective effects of regularization on inverse filtering. The regularization techniques implemented include frequency independent and dependent methods as well as a perceptually-motivated method. The subjective tests were based on the ITU-R MUSHRA method.
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