565 citations · 2.3k across the 35 of their papers we have counts for
9 papers · 1 filter
Neumann Optimizer: A Practical Optimization Algorithm for Deep Neural Networks
Shankar Krishnan, Ying Xiao, Rif A. Saurous
Progress in deep learning is slowed by the days or weeks it takes to train large models. The natural solution of using more hardware is limited by diminishing returns, and leads to…
On Using Backpropagation for Speech Texture Generation and Voice Conversion
Jan Chorowski, Ron J. Weiss, Rif A. Saurous +1
Inspired by recent work on neural network image generation which rely on backpropagation towards the network inputs, we present a proof-of-concept system for speech texture synthes…
Natural TTS Synthesis by Conditioning WaveNet on Mel Spectrogram Predictions
Jonathan Shen, Ruoming Pang, Ron J. Weiss +10
This paper describes Tacotron 2, a neural network architecture for speech synthesis directly from text. The system is composed of a recurrent sequence-to-sequence feature predictio…
TensorFlow Distributions
Joshua V. Dillon, Ian Langmore, Dustin Tran +7
The TensorFlow Distributions library implements a vision of probability theory adapted to the modern deep-learning paradigm of end-to-end differentiable computation. Building on tw…
Unsupervised Learning of Semantic Audio Representations
Aren Jansen, Manoj Plakal, Ratheet Pandya +5
Even in the absence of any explicit semantic annotation, vast collections of audio recordings provide valuable information for learning the categorical structure of sounds. We cons…
Uncovering Latent Style Factors for Expressive Speech Synthesis
Yuxuan Wang, RJ Skerry-Ryan, Ying Xiao +5
Prosodic modeling is a core problem in speech synthesis. The key challenge is producing desirable prosody from textual input containing only phonetic information. In this prelimina…
Fixing a Broken ELBO
Alexander A. Alemi, Ben Poole, Ian Fischer +3
Recent work in unsupervised representation learning has focused on learning deep directed latent-variable models. Fitting these models by maximizing the marginal likelihood or evid…
Tacotron: Towards End-to-End Speech Synthesis
Yuxuan Wang, RJ Skerry-Ryan, Daisy Stanton +11
A text-to-speech synthesis system typically consists of multiple stages, such as a text analysis frontend, an acoustic model and an audio synthesis module. Building these component…
Deep Probabilistic Programming
Dustin Tran, Matthew D. Hoffman, Rif A. Saurous +3
We propose Edward, a Turing-complete probabilistic programming language. Edward defines two compositional representations---random variables and inference. By treating inference as…