Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: DCCRN+: Channel-wise Subband DCCRN with SNR Estimation for Speech
  Enhancement   Deep complex convolution recurrent network (DCCRN), which extends CRN with
complex structure, has achieved superior performance in MOS evaluation in
Interspeech 2020 deep noise suppression challenge (DNS2020). This paper further
extends DCCRN with the following significant revisions. We first extend the
model to sub-band processing where the bands are split and merged by learnable
neural network filters instead of engineered FIR filters, leading to a faster
noise suppressor trained in an end-to-end manner. Then the LSTM is further
substituted with a complex TF-LSTM to better model temporal dependencies along
both time and frequency axes. Moreover, instead of simply concatenating the
output of each encoder layer to the input of the corresponding decoder layer,
we use convolution blocks to first aggregate essential information from the
encoder output before feeding it to the decoder layers. We specifically
formulate the decoder with an extra a priori SNR estimation module to maintain
good speech quality while removing noise. Finally a post-processing module is
adopted to further suppress the unnatural residual noise. The new model, named
DCCRN+, has surpassed the original DCCRN as well as several competitive models
in terms of PESQ and DNSMOS, and has achieved superior performance in the new
Interspeech 2021 DNS challenge

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The categories of this paper are: mtrl-th
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The categories of this paper are: bayes-an
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The categories of this paper are: astro-ph
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The categories of this paper are: physics
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The categories of this paper are: hep-lat
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The categories of this paper are: cond-mat
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The categories of this paper are: chem-ph
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The categories of this paper are: dg-ga
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The categories of this paper are: ao-sci
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The categories of this paper are: hep-th
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The categories of this paper are: patt-sol
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The categories of this paper are: math-ph
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The categories of this paper are: comp-gas
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The categories of this paper are: hep-ph
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The categories of this paper are: adap-org
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The categories of this paper are: math