A Literature Review of WaveNet: Theory, Application, and Optimization

Boilard J, Gournay P, Lefebvre R. A Literature Review of WaveNet: Theory, Application, and Optimization. In: AES Convention 146. Audio Engineering Society; 2019. Paper 10171. Available from: https://aes.org/publications/elibrary-page/?id=20304

@inproceedings{Boilard2019_20304,
  author = {Boilard, Jonathan and Gournay, Philippe and Lefebvre, Roch},
  title = {{A Literature Review of WaveNet: Theory, Application, and Optimization}},
  booktitle = {AES Convention 146},
  note = {Paper 10171},
  year = {2019},
  month = mar,
  publisher = {Audio Engineering Society},
  url = {https://aes.org/publications/elibrary-page/?id=20304}
}

TY  - CPAPER
TI  - A Literature Review of WaveNet: Theory, Application, and Optimization
AU  - Boilard, Jonathan
AU  - Gournay, Philippe
AU  - Lefebvre, Roch
T2  - AES Convention 146
M1  - Paper 10171
PY  - 2019
DA  - 2019/03/06
UR  - https://aes.org/publications/elibrary-page/?id=20304
PB  - Audio Engineering Society
LA  - en
AB  - WaveNet is a deep convolutional artificial neural network. It is also an autoregressive and probabilistic generative model; it is therefore by nature perfectly suited to solving various complex problems in speech processing. It already achieves state-of-the-art performance in text-to-speech synthesis. It also constitutes a radically new and remarkably efficient tool to perform voice transformation, speech enhancement, and speech compression. This paper presents a comprehensive review of the literature on WaveNet since its introduction in 2016. It identifies and discusses references related to its theoretical foundation, its application scope, and the possible optimization of its subjective quality and computational efficiency.
ER  -