2k citations · 4.6k across the 27 of their papers we have counts for
5 papers · 1 filter
Sample Efficient Adaptive Text-to-Speech
Yutian Chen, Yannis Assael, Brendan Shillingford +11
We present a meta-learning approach for adaptive text-to-speech (TTS) with few data. During training, we learn a multi-speaker model using a shared conditional WaveNet core and ind…
The challenge of realistic music generation: modelling raw audio at scale
Sander Dieleman, Aäron van den Oord, Karen Simonyan
Realistic music generation is a challenging task. When building generative models of music that are learnt from data, typically high-level representations such as scores or MIDI ar…
Associative Compression Networks for Representation Learning
Alex Graves, Jacob Menick, Aaron van den Oord
This paper introduces Associative Compression Networks (ACNs), a new framework for variational autoencoding with neural networks. The system differs from existing variational autoe…
Efficient Neural Audio Synthesis
Nal Kalchbrenner, Erich Elsen, Karen Simonyan +7
Sequential models achieve state-of-the-art results in audio, visual and textual domains with respect to both estimating the data distribution and generating high-quality samples. E…
Adversarial Risk and the Dangers of Evaluating Against Weak Attacks
Jonathan Uesato, Brendan O'Donoghue, Aaron van den Oord +1
This paper investigates recently proposed approaches for defending against adversarial examples and evaluating adversarial robustness. We motivate 'adversarial risk' as an objectiv…