Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Reverberant Audio Source Separation via Sparse and Low-Rank Modeling   The performance of audio source separation from underdetermined convolutive
mixture assuming known mixing filters can be significantly improved by using an
analysis sparse prior optimized by a reweighting l1 scheme and a wideband
datafidelity term, as demonstrated by a recent article. In this letter, we show
that the performance can be improved even more significantly by exploiting a
low-rank prior on the source spectrograms.We present a new algorithm to
estimate the sources based on i) an analysis sparse prior, ii) a reweighting
scheme so as to increase the sparsity, iii) a wideband data-fidelity term in a
constrained form, and iv) a low-rank constraint on the source spectrograms.
Evaluation on reverberant music mixtures shows that the resulting algorithm
improves state-of-the-art methods by more than 2 dB of signal-to-distortion
ratio.

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The categories of this paper are: astro-ph
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The categories of this paper are: alg-geom
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The categories of this paper are: q-fin
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The categories of this paper are: solv-int
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The categories of this paper are: funct-an
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The categories of this paper are: chem-ph
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The categories of this paper are: comp-gas
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The categories of this paper are: adap-org
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The categories of this paper are: q-bio
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The categories of this paper are: plasm-ph
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The categories of this paper are: nucl-ex
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The categories of this paper are: hep-ex
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The categories of this paper are: math-ph
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The categories of this paper are: mtrl-th
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The categories of this paper are: atom-ph
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The categories of this paper are: stat