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This paper addresses a new statistical model of binaural signals and its application to efficient binaural source separation. Binaural source separation is always required to retain a spatial cue of the separated sound, such as a head-related transfer function (HRTF). However, the direct use of an HRTF is not realistic because this information is normally not known in advance. To cope with this problem,...
In this paper, we address an optimization issue for the divergence in supervised nonnegative matrix factorization with spectrogram restoration, which has been proposed for addressing multichannel signal separation. This method separates non-target components and reconstructs some missing data caused by preceding spatial clustering via supervised basis extrapolation. In our previous study, we only...
In this paper, we propose a new approach for addressing music signal separation based on the generalized Bayesian estimator with automatic prior adaptation. This method consists of three parts, namely, the generalized MMSE-STSA estimator with a flexible target signal prior, the NMF-based dynamic interference spectrogram estimator, and closed-form parameter estimation for the statistical model of the...
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