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Informed Hybrid Primary Ambient Extraction for Spatial Audio Reproduction

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Spatial audio reproduction is essential to create a natural 3D listening experience for digital media. Primary ambient extraction (PAE) is an emerging technique that facilitates an efficient, flexible, and immersive spatial audio reproduction of channel-based audio for any arbitrary playback configurations. This paper presents a hybrid PAE method based on the weighted sum of several existing PAE methods. Using an extraction error performance prior, we derive the optimal weights to combine the candidate PAE methods. Two cases of the error performance are considered: the errors are mutually uncorrelated or partially correlated. Our simulation results indicate that the proposed hybrid PAE method that considers partial error correlation could yield even better performance than the best individual PAE method in any cases.

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