Automated audio quality prediction is still considered a challenge for stereo or multichannel signals carrying spatial information. A system that accurately and reliably predicts quality scores obtained by time-consuming listening tests can be of great advantage in saving resources, for instance, in the evaluation of parametric spatial audio codecs. Most of the solutions so far work with individual comparisons of distortions of interchannel cues across time and frequency, known to correlate to distortions in the evoked spatial image of the subject listener. We propose a scene analysis method that considers signal loudness distributed across estimations of perceived source directions on the horizontal plane. The calculation of distortion features in the directional loudness domain (as opposed to the time-frequency domain) seems to provide equal or better correlation with subjectively perceived quality degradation than previous methods, as con?rmed by experiments with an extensive database of parametric audio codec listening tests. We investigate the effect of a number of design alternatives (based on psychoacoustic principles) on the overall prediction performance of the associated quality measurement system.
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