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J. Boilard, P. Gournay, and R. Lefebvre, "A Literature Review of WaveNet: Theory, Application, and Optimization," Paper 10171, (2019 March.). doi: J. Boilard, P. Gournay, and R. Lefebvre, "A Literature Review of WaveNet: Theory, Application, and Optimization," Paper 10171, (2019 March.). doi:
Abstract: 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.

@article{boilard2019a,
author={boilard, jonathan and gournay, philippe and lefebvre, roch},
journal={journal of the audio engineering society},
title={a literature review of wavenet: theory, application, and optimization},
year={2019},
volume={},
number={},
pages={},
doi={},
month={march},} @article{boilard2019a,
author={boilard, jonathan and gournay, philippe and lefebvre, roch},
journal={journal of the audio engineering society},
title={a literature review of wavenet: theory, application, and optimization},
year={2019},
volume={},
number={},
pages={},
doi={},
month={march},
abstract={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.},}

TY - paper
TI - A Literature Review of WaveNet: Theory, Application, and Optimization
SP - EP -
AU - Boilard, Jonathan
AU - Gournay, Philippe
AU - Lefebvre, Roch
PY - 2019
JO - Journal of the Audio Engineering Society
IS -
VO -
VL -
Y1 - March 2019 TY - paper
TI - A Literature Review of WaveNet: Theory, Application, and Optimization
SP - EP -
AU - Boilard, Jonathan
AU - Gournay, Philippe
AU - Lefebvre, Roch
PY - 2019
JO - Journal of the Audio Engineering Society
IS -
VO -
VL -
Y1 - March 2019
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.