Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Neural Speech Synthesis on a Shoestring: Improving the Efficiency of
  LPCNet   Neural speech synthesis models can synthesize high quality speech but
typically require a high computational complexity to do so. In previous work,
we introduced LPCNet, which uses linear prediction to significantly reduce the
complexity of neural synthesis. In this work, we further improve the efficiency
of LPCNet -- targeting both algorithmic and computational improvements -- to
make it usable on a wide variety of devices. We demonstrate an improvement in
synthesis quality while operating 2.5x faster. The resulting open-source LPCNet
algorithm can perform real-time neural synthesis on most existing phones and is
even usable in some embedded devices.

16
The categories of this paper are: stat
36
The categories of this paper are: cmp-lg
5
The categories of this paper are: gr-qc
35
The categories of this paper are: mtrl-th
32
The categories of this paper are: atom-ph
2
The categories of this paper are: math
29
The categories of this paper are: funct-an
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The categories of this paper are: dg-ga
8
The categories of this paper are: hep-ex
33
The categories of this paper are: plasm-ph
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The categories of this paper are: q-fin
37
The categories of this paper are: supr-con
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The categories of this paper are: econ
25
The categories of this paper are: patt-sol
14
The categories of this paper are: math-ph
22
The categories of this paper are: chao-dyn