Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Monaural Speech Enhancement Using a Multi-Branch Temporal Convolutional
  Network   Deep learning has achieved substantial improvement on single-channel speech
enhancement tasks. However, the performance of multi-layer perceptions
(MLPs)-based methods is limited by the ability to capture the long-term
effective history information. The recurrent neural networks (RNNs), e.g., long
short-term memory (LSTM) model, are able to capture the long-term temporal
dependencies, but come with the issues of the high latency and the complexity
of training.To address these issues, the temporal convolutional network (TCN)
was proposed to replace the RNNs in various sequence modeling tasks. In this
paper we propose a novel TCN model that employs multi-branch structure, called
multi-branch TCN (MB-TCN), for monaural speech enhancement.The MB-TCN exploits
split-transform-aggregate design, which is expected to obtain strong
representational power at a low computational complexity.Inspired by the TCN,
the MB-TCN model incorporates one dimensional causal dilated CNN and residual
learning to expand receptive fields for capturing long-term temporal contextual
information.Our extensive experimental investigation suggests that the MB-TCNs
outperform the residual long short-term memory networks (ResLSTMs), temporal
convolutional networks (TCNs), and the CNN networks that employ dense
aggregations in terms of speech intelligibility and quality, while providing
superior parameter efficiency. Furthermore, our experimental results
demonstrate that our proposed MB-TCN model is able to outperform multiple
state-of-the-art deep learning-based speech enhancement methods in terms of
five widely used objective metrics.

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The categories of this paper are: comp-gas
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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: chao-dyn
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The categories of this paper are: hep-lat
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The categories of this paper are: q-bio
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The categories of this paper are: cond-mat
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The categories of this paper are: funct-an
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The categories of this paper are: math
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The categories of this paper are: supr-con
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The categories of this paper are: atom-ph
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The categories of this paper are: plasm-ph
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The categories of this paper are: chem-ph
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The categories of this paper are: cs
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The categories of this paper are: cmp-lg
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The categories of this paper are: math-ph