WaveGlow
A Flow-based Generative Network for Speech Synthesis
About
In our recent paper, we propose WaveGlow: a flow-based network capable of generating high quality speech from mel-spectrograms. WaveGlow combines insights from Glow and WaveNet in order to provide fast, efficient and high-quality audio synthesis, without the need for auto-regression. WaveGlow is implemented using only a single network, trained using only a single cost function: maximizing the likelihood of the training data, which makes the training procedure simple and stable.
Open Source Health
- Stars
- 2,339
- Forks
- 534
- License
- BSD-3-Clause
- Last commit
- 3 years ago
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NVIDIA
Publisher of DALI (NVIDIA Data Loading Library) and Tensorrt
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