为什么值得关注

它提供了从音频提取到语音生成的完整引导流程，完全在自有 GPU 上运行，隐私保护强，并支持零样模式无需训练即可即时克隆。

适合谁使用

构建自定义语音界面的开发者
需要个性化配音的内容创作者
探索少样本语音适配的研究人员
希望避免云端服务的隐私敏感用户

典型使用场景

为自己的数字助手克隆声音
用个性化风格生成有声书
为个人视频项目配音
为无障碍工具创建语音旁白

项目优势

完全本地运行，数据不离开你的机器
单命令即可完成提取、清洗、转录和训练全流程
零样模式支持单条音频即时克隆
提供包含四个标签页的网页界面，覆盖所有 CLI 功能

使用前须知

需要 Linux 系统并配备 NVIDIA CUDA GPU，训练至少需要 24 GB 显存
语音质量高度依赖干净的源音频和仔细的转录校对
目前依赖 Qwen3-TTS 基础模型，可能无法在非 CUDA 硬件上运行

README 快速开始

Voice Clone Lab

Clone a voice from a few minutes of audio and generate speech from text — locally, on your own GPU. Give it 5–15 minutes of clean speech (a recording, or a YouTube link) and it fine-tunes Qwen3-TTS into a personal voice model you can drive from a CLI or a web UI.

Any source: upload a recording, record from your mic, or paste a YouTube/URL link
Guided pipeline: extract → clean → split → transcribe → proofread in an editable table → train
Your voices, organized by name: train as many as you like, pick one and type text
Zero-shot mode: try a voice instantly from a single clip, no training
Fully local: audio, transcripts, and voice models never leave your machine

Consent notice

Use this project only for your own voice or a voice where you have explicit written permission from the speaker. Do not use it for impersonation, fraud, bypassing consent, harassment, or cloning public figures or private people without permission. The same rule applies to URLs: only download content you have the rights to use.

Requirements

Linux with an NVIDIA CUDA GPU
Training: 24 GB VRAM minimum (RTX 3090/4090 class, batch-size 2). 32 GB+ is comfortable.
Generation only (using a checkpoint someone else trained): any ~8 GB card works.
Python ≥ 3.10 (3.12 recommended), ffmpeg, git

Install

git clone https://github.com/tetsuo-ai/voice_clone_lab.git
cd voice_clone_lab

pip install -e '.[ui]'     # core + web UI; drop [ui] for CLI-only
vcl setup --download       # fetch Qwen3-TTS (pinned + patched) and the 1.7B base weights (~4 GB)
vcl check                  # verify your machine is ready

Optional extras: pip install -e '.[asr,yt,vad,denoise,dev]' — WhisperX (word timestamps), yt-dlp (URL sources), WebRTC VAD (better chunking), mild denoising, and the test suite.

Quickstart

1. Get some audio of your voice

Record 5–15 minutes in a quiet room, one mic, natural reading pace (ready-made reading text: recording_scripts/voice_dataset_reading_script.txt). Or skip recording and paste a link to something you're in:

vcl run --speaker alex --input "https://www.youtube.com/watch?v=…"
# or a local file (wav/mp4/m4a/mp3):
vcl run --speaker alex --input ~/recordings/alex.wav

That one command extracts, cleans, splits, transcribes, and

项目描述

Clone a voice from a few minutes of audio and generate speech locally — Qwen3-TTS fine-tuning pipeline with CLI and web UI

voice_clone_lab