Abstract
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Perceptually accurate representation of audio objects obtained from multi-track audio signals is desired for applications such as interactive soundfield rendering and browsing. Presented in this work is a scalable psychoacoustic analysis-by-synthesis approach to extract the perceptually dominant time-frequency audio objects from a multi-track audio signal. The proposed compression framework exploits sparsity in the perceptual time-frequency domain where up to eight audio objects can be efficiently encoded using only two audio mixtures with side information representing the origin of the time-frequency instances in the mixture signals. The proposed approach, judged by both objective and subjective tests, results in superior audio quality compared to existing techniques when encoding more than 5 audio objects.