Parallel WaveNet: Fast High-Fidelity Speech Synthesis

@inproceedings{Oord2018ParallelWF,
  title={Parallel WaveNet: Fast High-Fidelity Speech Synthesis},
  author={A{\"a}ron van den Oord and Yazhe Li and Igor Babuschkin and Karen Simonyan and Oriol Vinyals and Koray Kavukcuoglu and George van den Driessche and Edward Lockhart and Luis C. Cobo and Florian Stimberg and Norman Casagrande and Dominik Grewe and Seb Noury and Sander Dieleman and Erich Elsen and Nal Kalchbrenner and Heiga Zen and Alex Graves and Helen King and Tom Walters and Dan Belov and Demis Hassabis},
  booktitle={ICML},
  year={2018}
}
The recently-developed WaveNet architecture [27] is the current state of the art in realistic speech synthesis, consistently rated as more natural sounding for many different languages than any previous system. However, because WaveNet relies on sequential generation of one audio sample at a time, it is poorly suited to today’s massively parallel computers, and therefore hard to deploy in a real-time production setting. This paper introduces Probability Density Distillation, a new method for… CONTINUE READING
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