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Boosting Star-GANs for Voice Conversion with Contrastive Discriminator. (arXiv:2209.10088v2 [eess.AS] UPDATED)
Sept. 23, 2022, 1:12 a.m. | Shijing Si, Jianzong Wang, Xulong Zhang, Xiaoyang Qu, Ning Cheng, Jing Xiao
cs.LG updates on arXiv.org arxiv.org
Nonparallel multi-domain voice conversion methods such as the StarGAN-VCs
have been widely applied in many scenarios. However, the training of these
models usually poses a challenge due to their complicated adversarial network
architectures. To address this, in this work we leverage the state-of-the-art
contrastive learning techniques and incorporate an efficient Siamese network
structure into the StarGAN discriminator. Our method is called
SimSiam-StarGAN-VC and it boosts the training stability and effectively
prevents the discriminator overfitting issue in the training process. We …
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