We test the performance of GAN models for lip-synchronization. For this, we reimplement LipGAN in Pytorch, train it on the dataset GRID and compare it to our own variation, L1WGAN-GP, adapted to the LipGAN architecture and also trained on GRID.

翻译：我们测试GAN的唇同步模型的性能,为此,我们在Pytorch实施LipGAN, 培训它使用全球资源数据库数据集,并将其与我们自己的变异(L1WGAN-GP)进行比较,改编成LipGAN结构,并接受全球资源数据库培训。