Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Neural ODE with Temporal Convolution and Time Delay Neural Networks for
  Small-Footprint Keyword Spotting   In this paper, we propose neural network models based on the neural ordinary
differential equation (NODE) for small-footprint keyword spotting (KWS). We
present techniques to apply NODE to KWS that make it possible to adopt Batch
Normalization to NODE-based network and to reduce the number of computations
during inference. Finally, we show that the number of model parameters of the
proposed model is smaller by 68% than that of the conventional KWS model.

29
The categories of this paper are: funct-an
31
The categories of this paper are: ao-sci
18
The categories of this paper are: econ
35
The categories of this paper are: mtrl-th
10
The categories of this paper are: q-bio
34
The categories of this paper are: chem-ph
24
The categories of this paper are: dg-ga
16
The categories of this paper are: stat
15
The categories of this paper are: nucl-ex
8
The categories of this paper are: hep-ex
21
The categories of this paper are: adap-org
2
The categories of this paper are: math
27
The categories of this paper are: comp-gas
33
The categories of this paper are: plasm-ph
12
The categories of this paper are: nucl-th
23
The categories of this paper are: solv-int