Methods › Audio › Generative Audio Models › WaveGrad
WaveGrad
Introduced by Nanxin Chen et al. in WaveGrad: Estimating Gradients for Waveform Generation
archive 2025-07-28 Description, source and code snippet are the archive's method entry.
WaveGrad is a conditional model for waveform generation through estimating gradients of the data density. This model is built on the prior work on score matching and diffusion probabilistic models. It starts from Gaussian white noise and iteratively refines the signal via a gradient-based sampler conditioned on the mel-spectrogram. WaveGrad is non-autoregressive, and requires only a constant number of generation steps during inference. It can use as few as 6 iterations to generate high fidelity audio samples.
Papers archive 2025-07-28
7 shown of 7, newest first. Repository counts are the archive's code-links table. A Syntology line states what Syntology ran from that paper's harvested code; it is per sample and not a correctness claim.
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GLA-Grad: A Griffin-Lim Extended Waveform Generation Diffusion Model 9 Feb 2024 · 0 repositories · arXiv:2402.15516
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BDDM: Bilateral Denoising Diffusion Models for Fast and High-Quality Speech Synthesis 25 Mar 2022 · 1 repository · arXiv:2203.13508Syntology ran 5 of 6 samples · 1 unverified
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InferGrad: Improving Diffusion Models for Vocoder by Considering Inference in Training 8 Feb 2022 · 0 repositories · arXiv:2202.03751
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Quasi-Taylor Samplers for Diffusion Generative Models based on Ideal Derivatives 26 Dec 2021 · 0 repositories · arXiv:2112.13339
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VocBench: A Neural Vocoder Benchmark for Speech Synthesis 6 Dec 2021 · 1 repository · arXiv:2112.03099
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WaveGrad 2: Iterative Refinement for Text-to-Speech Synthesis 17 Jun 2021 · 3 repositories · arXiv:2106.09660Syntology ran 2 of 2 samples · 0 unverified
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WaveGrad: Estimating Gradients for Waveform Generation 2 Sep 2020 · 7 repositories · arXiv:2009.00713Syntology ran 1 of 3 samples · 2 unverified · 1 pointer-only (licence)
Tasks archive 2025-07-28
6 tasks the archive attaches to papers tagged with this method, by distinct papers. A task without a page in the catalog is plain text.
| Task | Papers |
|---|---|
| Speech Synthesis | 5 |
| Denoising | 2 |
| Image Generation | 2 |
| Text-To-Speech Synthesis | 2 |
| Text to Speech | 1 |
| text-to-speech | 1 |
Usage over time archive 2025-07-28
Components: the archive holds no method-to-method composition, so PwC's Components table cannot be rebuilt; the Papers list carries no Results column for the same reason (the archive does not join its leaderboard rows to method tags).
Categories archive 2025-07-28
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