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RVC

Retrieval-based voice conversion WebUI — train AI voice models with just 10 minutes of audio

★ 36,196 GitHub MIT voice-conversionvoice-cloningai-voiceaudiottsdeepfake-voice Bild & Video

Überblick

RVC (Retrieval-based Voice Conversion) is a powerful open-source voice conversion framework with a WebUI that lets you train high-quality AI voice models using as little as 10 minutes of voice data. With over 36,000 GitHub stars, it has become the de facto standard for AI voice cloning and conversion. RVC uses a retrieval-based approach combined with content features from HuBERT and Wav2Vec2 to achieve remarkable voice conversion quality while preserving the emotional expression and prosody of the source audio. It supports real-time voice conversion, batch processing, text-to-speech integration, and includes a built-in model training pipeline. The WebUI provides an intuitive interface for managing models, processing audio, and performing voice conversion without writing code. RVC runs on consumer GPUs with as little as 4GB VRAM and supports both Windows and Linux deployments via Docker.

Anforderungen

Min vCPU
2
Min RAM
4096 MB
Min Disk
10 GB
Rec vCPU
4
Rec RAM
8192 MB
Rec Disk
20 GB

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Docker Compose

# Generated by Run This Ai — docker-compose.yml
services:
  rvc:
    image: thaomike/rvc:latest
    restart: unless-stopped
    ports:
      - 8080:8080
    volumes:
      - ./data/rvc:/data

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Anleitungen & Artikel

How to Deploy RVC Voice Conversion with Docker: Complete Step-by-Step Tutorial

From pulling the Docker image to training your first AI voice model and performing real-time conversion — this tutorial covers every step of deploying RVC with Docker.

Jun 29, 2026

RVC: The Open-Source Voice Cloning Tool With 36k Stars That Needs Only 10 Minutes of Audio

RVC (Retrieval-based Voice Conversion) is the community standard for AI voice cloning. Train high-quality voice models with just 10 minutes of audio. Here's what makes it special and how to get started.

Jun 29, 2026