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Object-Based Audio Coding Using Non-Negative Matrix Factorization for the Spectrogram Representation

This paper proposes a new object-based audio coding algorithm, which uses non-negative matrix factorization (NMF) for the magnitude spectrogram representation and the phase information is coded separately. The magnitude model is obtained using a perceptually weighted NMF algorithm, which minimizes the noise-to-mask ratio (NMR) of the decomposition, and is able to utilize long term redundancy by an object-based representation. Methods for the quantization and entropy coding of the NMF representation parameters are proposed, and the quality loss is evaluated using the NMR measure. The quantization of the phase information is also studied. Additionally we propose a sparseness criteria for the NMF algorithm, which is set to favor the gain values having the highest probability and thus the shortest entropy coding word length, resulting to a reduced bitrate.

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