This demo presents WaveNet, a deep generative model of raw audio waveforms. We show that WaveNets are able to generate speech which mimics any human voice and which sounds more natural than the best existing Text-to-Speech (TTS) systems, reducing the gap in subjective quality relative to natural speech by over 50%. We also demonstrate that the same network can be used to synthesize other audio signals such as music, and present some striking samples of automatically generated piano pieces. WaveNets open up a lot of possibilities for text-to-speech, music generation and audio modelling in general.
Cite as: van den Oord, A., Dieleman, S., Zen, H., Simonyan, K., Vinyals, O., Graves, A., Kalchbrenner, N., Senior, A., Kavukcuoglu, K. (2016) WaveNet: A Generative Model for Raw Audio. Proc. 9th ISCA Workshop on Speech Synthesis Workshop (SSW 9), 125
@inproceedings{vandenoord16_ssw,
author={Aäron {van den Oord} and Sander Dieleman and Heiga Zen and Karen Simonyan and Oriol Vinyals and Alex Graves and Nal Kalchbrenner and Andrew Senior and Koray Kavukcuoglu},
title={{WaveNet: A Generative Model for Raw Audio}},
year=2016,
booktitle={Proc. 9th ISCA Workshop on Speech Synthesis Workshop (SSW 9)},
pages={125}
}