no code implementations • 26 Oct 2022 • Vasily Zadorozhnyy, Qiang Ye, Kazuhito Koishida
In recent years, Generative Adversarial Networks (GANs) have produced significantly improved results in speech enhancement (SE) tasks.
Ranked #1 on Speech Enhancement on VoiceBank + DEMAND
1 code implementation • 28 Sep 2022 • Cole Pospisil, Vasily Zadorozhnyy, Qiang Ye
Methods such as Layer Normalization (LN) and Batch Normalization (BN) have proven to be effective in improving the training of Recurrent Neural Networks (RNNs).
1 code implementation • 12 Aug 2022 • Edison Mucllari, Vasily Zadorozhnyy, Cole Pospisil, Duc Nguyen, Qiang Ye
In recent years, using orthogonal matrices has been shown to be a promising approach in improving Recurrent Neural Networks (RNNs) with training, stability, and convergence, particularly, to control gradients.
2 code implementations • 3 Mar 2022 • Kehelwala Dewage Gayan Maduranga, Vasily Zadorozhnyy, Qiang Ye
We consider Convolutional Neural Networks (CNNs) with 2D structured features that are symmetric in the spatial dimensions.
1 code implementation • CVPR 2021 • Vasily Zadorozhnyy, Qiang Cheng, Qiang Ye
Generative adversarial network (GAN) has become one of the most important neural network models for classical unsupervised machine learning.
Ranked #4 on Conditional Image Generation on CIFAR-100