Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: CycleGAN Voice Conversion of Spectral Envelopes using Adversarial
  Weights   This paper tackles GAN optimization and stability issues in the context of
voice conversion. First, to simplify the conversion task, we propose to use
spectral envelopes as inputs. Second we propose two adversarial weight training
paradigms, the generalized weighted GAN and the generator impact GAN, both aim
at reducing the impact of the generator on the discriminator, so both can learn
more gradually and efficiently during training. Applying an energy constraint
to the cycleGAN paradigm considerably improved conversion quality. A subjective
experiment conducted on a voice conversion task on the voice conversion
challenge 2018 dataset shows first that despite a significantly reduced network
complexity, the proposed method achieves state-of-the-art results, and second
that the proposed weighted GAN methods outperform a previously proposed one.

22
The categories of this paper are: chao-dyn
18
The categories of this paper are: econ
13
The categories of this paper are: quant-ph
31
The categories of this paper are: ao-sci
27
The categories of this paper are: comp-gas
3
The categories of this paper are: physics
23
The categories of this paper are: solv-int
37
The categories of this paper are: supr-con
15
The categories of this paper are: nucl-ex
21
The categories of this paper are: adap-org
5
The categories of this paper are: gr-qc
4
The categories of this paper are: cond-mat
32
The categories of this paper are: atom-ph
24
The categories of this paper are: dg-ga
33
The categories of this paper are: plasm-ph
34
The categories of this paper are: chem-ph