599 citations · 1.2k across the 7 of their papers we have counts for
7 papers
NU-GAN: High resolution neural upsampling with GAN
Rithesh Kumar, Kundan Kumar, Vicki Anand +2
In this paper, we propose NU-GAN, a new method for resampling audio from lower to higher sampling rates (upsampling). Audio upsampling is an important problem since productionizing…
MelGAN: Generative Adversarial Networks for Conditional Waveform Synthesis
Kundan Kumar, Rithesh Kumar, Thibault de Boissiere +6
Previous works (Donahue et al., 2018a; Engel et al., 2019a) have found that generating coherent raw audio waveforms with GANs is challenging. In this paper, we show that it is poss…
ObamaNet: Photo-realistic lip-sync from text
Rithesh Kumar, Jose Sotelo, Kundan Kumar +2
We present ObamaNet, the first architecture that generates both audio and synchronized photo-realistic lip-sync videos from any new text. Contrary to other published lip-sync appro…
On Random Weights for Texture Generation in One Layer Neural Networks
Mihir Mongia, Kundan Kumar, Akram Erraqabi +1
Recent work in the literature has shown experimentally that one can use the lower layers of a trained convolutional neural network (CNN) to model natural textures. More interesting…
SampleRNN: An Unconditional End-to-End Neural Audio Generation Model
Soroush Mehri, Kundan Kumar, Ishaan Gulrajani +5
In this paper we propose a novel model for unconditional audio generation based on generating one audio sample at a time. We show that our model, which profits from combining memor…
PixelVAE: A Latent Variable Model for Natural Images
Ishaan Gulrajani, Kundan Kumar, Faruk Ahmed +4
Natural image modeling is a landmark challenge of unsupervised learning. Variational Autoencoders (VAEs) learn a useful latent representation and model global structure well but ha…