25 citations · 28 across the 3 of their papers we have counts for
6 papers
Topological Regularization for Graph Neural Networks Augmentation
Rui Song, Fausto Giunchiglia, Ke Zhao +1
The complexity and non-Euclidean structure of graph data hinder the development of data augmentation methods similar to those in computer vision. In this paper, we propose a featur…
DiffWave: A Versatile Diffusion Model for Audio Synthesis
Zhifeng Kong, Wei Ping, Jiaji Huang +2
In this work, we propose DiffWave, a versatile diffusion probabilistic model for conditional and unconditional waveform generation. The model is non-autoregressive, and converts th…
A property in vector-valued function spaces
Kexin Zhao, Dongni Tan
This paper deals with a property which is equivalent to generalised-lushness for separable spaces. It thus may be seemed as a geometrical property of a Banach space which ensures t…
WaveFlow: A Compact Flow-based Model for Raw Audio
Wei Ping, Kainan Peng, Kexin Zhao +1
In this work, we propose WaveFlow, a small-footprint generative flow for raw audio, which is directly trained with maximum likelihood. It handles the long-range structure of 1-D wa…
Multi-Speaker End-to-End Speech Synthesis
Jihyun Park, Kexin Zhao, Kainan Peng +1
In this work, we extend ClariNet (Ping et al., 2019), a fully end-to-end speech synthesis model (i.e., text-to-wave), to generate high-fidelity speech from multiple speakers. To mo…
Non-Autoregressive Neural Text-to-Speech
Kainan Peng, Wei Ping, Zhao Song +1
In this work, we propose ParaNet, a non-autoregressive seq2seq model that converts text to spectrogram. It is fully convolutional and brings 46.7 times speed-up over the lightweigh…