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auspicious3000/autovc

AutoVC: Zero-Shot Voice Style Transfer with Only Autoencoder Loss observed · 2026-08-28

github.com/auspicious3000/autovc · homepage · Python · MIT (permissive) observed · 2026-08-28

Health v2 · maintenance only

32/100

  • Activity 0
  • Release rhythm 35
  • Longevity 100

Flags: no_releases

How is this computed?

round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-03. Adoption (stars, forks) is never an input.

  • gap_med: n/a
  • age_days: 2668
  • days_rel: n/a
  • days_push: 680
  • n_releases_24m: 0

Full methodology

Adoption not part of the score

1100 stars · 215 forks observed · 2026-08-28

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

AUTOVC is a PyTorch implementation of a many-to-many non-parallel voice conversion framework that performs zero-shot voice style transfer using only an autoencoder with a carefully designed bottleneck. It includes pre-trained models, notebook-based conversion pipelines, and a WaveNet/HiFi-GAN vocoder for waveform synthesis.

Use cases

  • convert a voice recording to sound like a target speaker
  • perform zero-shot voice conversion without target speaker training data
  • do many-to-many voice conversion from non-parallel speech data
  • retrain a voice conversion model on my own speech dataset
  • synthesize waveforms from mel-spectrograms with a vocoder
  • reproduce the ICML 2019 AutoVC paper results

When to choose

  • you need research-grade non-parallel or zero-shot voice conversion in PyTorch
  • you want pre-trained models to convert voices without training from scratch
  • you are reproducing or building on the AutoVC paper

When to avoid

  • you need real-time or production voice conversion with modern quality
  • you want a maintained tool with active support
  • you need text-to-speech rather than voice-to-voice conversion

Facets

library · maturity maintenance

machine-learning audio-processing speech-recognition speech-processing machine-learning artificial-intelligence python voice-conversion speech-synthesis autoencoder zero-shot pytorch wavenet-vocoder style-transfer audio

6 sources

Member repositories

RepositoryRoleHealth v2
auspicious3000/autovcmain32

For agents

markdown · JSON · MCP: product_card(name="auspicious3000/autovc")

Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem