Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Audio-visual Speech Enhancement Using Conditional Variational
  Auto-Encoders   Variational auto-encoders (VAEs) are deep generative latent variable models
that can be used for learning the distribution of complex data. VAEs have been
successfully used to learn a probabilistic prior over speech signals, which is
then used to perform speech enhancement. One advantage of this generative
approach is that it does not require pairs of clean and noisy speech signals at
training. In this paper, we propose audio-visual variants of VAEs for
single-channel and speaker-independent speech enhancement. We develop a
conditional VAE (CVAE) where the audio speech generative process is conditioned
on visual information of the lip region. At test time, the audio-visual speech
generative model is combined with a noise model based on nonnegative matrix
factorization, and speech enhancement relies on a Monte Carlo
expectation-maximization algorithm. Experiments are conducted with the recently
published NTCD-TIMIT dataset as well as the GRID corpus. The results confirm
that the proposed audio-visual CVAE effectively fuses audio and visual
information, and it improves the speech enhancement performance compared with
the audio-only VAE model, especially when the speech signal is highly corrupted
by noise. We also show that the proposed unsupervised audio-visual speech
enhancement approach outperforms a state-of-the-art supervised deep learning
method.

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The categories of this paper are: cond-mat
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The categories of this paper are: nucl-th
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The categories of this paper are: comp-gas
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The categories of this paper are: stat
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The categories of this paper are: math-ph
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The categories of this paper are: cmp-lg
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The categories of this paper are: nucl-ex
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The categories of this paper are: chao-dyn
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The categories of this paper are: dg-ga
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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: math
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The categories of this paper are: adap-org
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The categories of this paper are: patt-sol
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The categories of this paper are: quant-ph
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The categories of this paper are: atom-ph