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For the task of monaural speech enhancement, A version of Sparse Nonnegative matrix factorization (Sparse NMF) using improved Alternating Direction Method of Multipliers (IADMM) with generalized Kullback-Leibler divergence is proposed. In this paper, an alternating direction method of multipliers (ADMM) for NMF is studied, which deals with the NMF problem using the cost function of beta divergence...
Mask estimate is regarded as the main goal for using the computational auditory scene analysis method to enhance speech contaminated by noises. This paper presents extended robust principal component analysis (RPCA) methods, referred to as NRPCA and ISNRPCA, to estimate mask effectively. The perceptually motivated cochleagram is decomposed into sparse and low-rank components via NRPCA or ISNRPCA,...
A perceptually motivated speech enhancement approach is proposed in this paper. Different from the conventional sparse and low-rank model based approaches, this new approach takes into account the perceptual differences in different frequency bands of the human auditory system, and separates speech from background noises in the Mel spectral domain. After two propositions for the Mel frequency weighted...
In order to exploit the inherent cyclostationary properties which vary periodically in most man-made signals, one prerequisite is the knowledge of the signal's cyclic autocorrelation (CA) which can be estimated from finite time-domain samples. In this paper we concern about the sparse, periodic CA estimation and focus on recovering the CA using compressive sampling, i.e. a small amount of time-domain...
In order to exploit the inherent cyclostationary properties which vary periodically in most man-made signals, one prerequisite is the knowledge of the signal's cyclic autocorrelation (CA) which can be estimated from finite time-domain samples. In this paper we concern about the sparse, periodic CA estimation and focus on recovering the CA using compressive sampling, i.e. a small amount of time-domain...
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