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Upmixing consists in extracting audio objects out of their downmix, given some parameters computed beforehand at a coding stage. It is an important task in audio processing with many applications in the entertainment industry. One particularly successful approach for this purpose is to compress the audio objects through nonnegative matrix factorization (NMF) parameters at the coder, to be used for...
Nonnegative matrix factorization (NMF) is a widely used method for audio source separation. Additional constraints supporting e.g. temporal continuity or sparseness adapt NMF to the structure of audio signals even further. In this paper, we propose generalized NMF constraints which make use of prior information gathered for each component individually. In general, this information could be obtained...
Nonnegative Matrix Factorization (NMF) is a well suited and widely used method for monaural sound source separation. It has been shown, that an additional cost term supporting temporal continuity can improve the separation quality [1]. We extend this model by adding a cost term, that penalizes large variations in the spectral dimension. We propose two different cost terms for this purpose and also...
ICA (Independent Component Analysis) is a mathematical tool traditionally employed for source separation. In this paper, we test its ability for texture analysis, in order to provide a new texture classification method. From the multitude of the existing algorithms, we have chosen FastICA, a version based on the forth order statistics of the analyzed signal. By FastICA, a texture is decomposed in...
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