chrisdonahue/wavegan

Health v2 · maintenance only

Flags: no_releases

Adoption not part of the score

1383 stars · 280 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

Official TensorFlow implementation of WaveGAN, a generative adversarial network that learns to synthesize raw audio waveforms from examples. It also includes SpecGAN, a spectrogram-based GAN alternative, and supports training on arbitrary audio files up to 4 seconds at 16kHz.

Use cases

• generate realistic sound effects with a GAN
• synthesize speech or bird vocalizations from raw audio
• train a generative model on a folder of WAV or MP3 files
• reproduce the WaveGAN paper results on the SC09 dataset
• compare waveform GANs against spectrogram-based GANs for audio generation

When to choose

• you want to generate short raw audio clips with a GAN
• you need the reference implementation of the WaveGAN paper
• you have a GPU and can work with TensorFlow 1.x

When to avoid

• you need modern TensorFlow 2.x or PyTorch support
• you need to generate audio longer than 4 seconds
• you want a production-ready audio synthesis pipeline rather than research code

Facets

library · maturity maintenance

machine-learning deep-learning audio-processing machine-learning deep-learning python gan audio-generation tensorflow waveform-synthesis research-code specgan audio gpu linux

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markdown · JSON · MCP: product_card(name="chrisdonahue/wavegan")