Methods › Audio › Generative Audio Models › WaveGAN

WaveGAN

30 papers tagged archive 2025-07-28

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.

WaveGAN is a generative adversarial network for unsupervised synthesis of raw-waveform audio (as opposed to image-like spectrograms).

The WaveGAN architecture is based off DCGAN. The DCGAN generator uses the transposed convolution operation to iteratively upsample low-resolution feature maps into a high-resolution image. WaveGAN modifies this transposed convolution operation to widen its receptive field, using a longer one-dimensional filters of length 25 instead of two-dimensional filters of size 5x5, and upsampling by a factor of 4 instead of 2 at each layer. The discriminator is modified in a similar way, using length-25 filters in one dimension and increasing stride from 2 to 4. These changes result in WaveGAN having the same number of parameters, numerical operations, and output dimensionality as DCGAN. An additional layer is added afterwards to allow for more audio samples. Further changes include:

  1. Flattening 2D convolutions into 1D (e.g. 5x5 2D conv becomes length-25 1D).
  2. Increasing the stride factor for all convolutions (e.g. stride 2x2 becomes stride 4).
  3. Removing batch normalization from the generator and discriminator.
  4. Training using the WGAN-GP strategy.
PaperSource

Papers archive 2025-07-28

30 shown of 30, 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.

Tasks archive 2025-07-28

20 shown of 29 tasks the archive attaches to papers tagged with this method, by distinct papers. A task without a page in the catalog is plain text.

TaskPapers
Text to Speech9
text-to-speech9
Generative Adversarial Network7
Speech Synthesis4
Vocal Bursts Intensity Prediction4
Image Generation3
Voice Conversion3
Audio Generation2
CPU2
Decoder2
GPU2
Singing Voice Synthesis2
Translation2
Adversarial Robustness1
Audio Synthesis1
Automatic Speech Recognition1
Automatic Speech Recognition (ASR)1
Image-to-Image Translation1
Speaker Recognition1
Spectral Reconstruction1

Usage over time archive 2025-07-28

Papers per year tagged with WaveGAN: 2018 to 2024, peak 10 10 0 2018: 1 paper 2018 2019: 2 papers 2019 2020: 8 papers 2020 2021: 10 papers 2021 2022: 6 papers 2022 2023: 1 paper 2023 2024: 2 papers 2024
Papers per year the archive tags with this method, by the paper's archive date (30 dated). Bars are counts, not a trend claim.

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

Generative Audio Models

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