An analysis of perceptual artifacts in MPEG scalable audio coding

We study coding artifacts in MPEG-compressed scalable audio. Specifically, we consider the MPEG advanced audio coder (AAC) using bit slice scalable arithmetic coding (BSAC) as implemented in the MPEG 4 reference software. First, we perform human subjective testing using the comparison category rating (CCR) approach, quantitatively comparing the performance of scalable BSAC with the nonscalable TwinVQ and AAC algorithms. This testing indicates that scalable BSAC performs very poorly relative to TwinVQ at the lowest bitrate considered (16 kb/s), largely because of an annoying and seemingly random mid-range tonal signal that is superimposed onto the desired output. In order to understand better and quantify perceptually the various forms of distortion introduced into compressed audio at low bit rates, we apply two analysis techniques: Reng probing and time-frequency decomposition. The Reng probing technique is capable of separating the linear time-invariant component of a multirate system from its nonlinear and periodically time-varying components. Using this technique, we conclude that aliasing is probably not the cause of the annoying tonal signal; instead, time-frequency analysis indicates that its cause is most likely suboptimal bit allocation.