Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Full Attention Bidirectional Deep Learning Structure for Single Channel
  Speech Enhancement   As the cornerstone of other important technologies, such as speech
recognition and speech synthesis, speech enhancement is a critical area in
audio signal processing. In this paper, a new deep learning structure for
speech enhancement is demonstrated. The model introduces a "full" attention
mechanism to a bidirectional sequence-to-sequence method to make use of latent
information after each focal frame. This is an extension of the previous
attention-based RNN method. The proposed bidirectional attention-based
architecture achieves better performance in terms of speech quality (PESQ),
compared with OM-LSA, CNN-LSTM, T-GSA and the unidirectional attention-based
LSTM baseline.

23
The categories of this paper are: solv-int
2
The categories of this paper are: math
27
The categories of this paper are: comp-gas
3
The categories of this paper are: physics
5
The categories of this paper are: gr-qc
16
The categories of this paper are: stat
12
The categories of this paper are: nucl-th
37
The categories of this paper are: supr-con
8
The categories of this paper are: hep-ex
0
The categories of this paper are: hep-ph
31
The categories of this paper are: ao-sci
15
The categories of this paper are: nucl-ex
28
The categories of this paper are: alg-geom
20
The categories of this paper are: acc-phys
11
The categories of this paper are: hep-lat
33
The categories of this paper are: plasm-ph