Methods › Audio › Generative Audio Models › SpecGAN
SpecGAN
Introduced by Chris Donahue et al. in Adversarial Audio Synthesis
archive 2025-07-28 Description, source and code snippet are the archive's method entry.
SpecGAN is a generative adversarial network method for spectrogram-based, frequency-domain audio generation. The problem is suited for GANs designed for image generation. The model can be approximately inverted.
To process audio into suitable spectrograms, the authors perform the short-time Fourier transform with 16 ms windows and 8ms stride, resulting in 128 frequency bins, linearly spaced from 0 to 8 kHz. They take the magnitude of the resultant spectra and scale amplitude values logarithmically to better-align with human perception. They then normalize each frequency bin to have zero mean and unit variance. They clip the spectra to $3$ standard deviations and rescale to [−1, 1].
They then use the DCGAN approach on the result spectra.
Papers archive 2025-07-28
1 shown of 1, 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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Adversarial Audio Synthesis 12 Feb 2018 · 22 repositories · arXiv:1802.04208Syntology ran 2 of 4 samples · 2 unverified · 4 pointer-only (licence)
Tasks archive 2025-07-28
3 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 |
|---|---|
| Audio Generation | 1 |
| Audio Synthesis | 1 |
| Image Generation | 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
Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections