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An Automatic Mixing System for Multitrack Spatialization for Stereo Based on Unmasking and Best Panning Practices

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One of the most important tasks in audio production is to place sound sources across the stereo field so as to reduce masking and immerse the listener within the space. This process of panning sources of a multitrack recording to achieve spatialization and masking minimization is a challenging optimization problem, mainly because of the complexity of auditory perception. We propose a novel panning system that makes use of a common framework for spectral decomposition, masking detection, multitrack sub-grouping and frequency-based spreading. It creates a well spatialized mix with increased clarity while complying to the best panning practices. Both real-time and offline optimization-based approaches are designed and implemented. We investigate the reduction of inter-track auditory masking using the MPEG psychoacoustic model along with various other masking and spatialization metrics extended for multitrack content. Subjective and objective tests compare the proposed work against mixes by professional sound engineers and existing auto-mix systems.

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AES - Audio Engineering Society