LiveTranslate

TheDeathDragonMIT活跃维护

抓取系统音频和麦克风,用 Whisper/SenseVoice 做语音识别,再通过 LLM API 流式翻译并实时显示字幕,适合主播、VTuber 和看外语视频时用。

Real-time audio translation, captures system audio + mic, runs ASR (Whisper/SenseVoice), translates via LLM API with streaming display. Perfect for VTubers, livestreamers, and watching foreign content. Windows 实时音频翻译,ASR 语音识别后 LLM 流式翻译显示,适合 VTuber、主播和外语视频观看。

v2026.08.17.1发布于 2026-08-17 02:56 UTC895star66fork同步于 2026-11-07 07:30 UTC

怎么上手

由 README 提炼,执行前请确认
git clone https://github.com/TheDeathDragon/LiveTranslate.git
cd LiveTranslate
install.bat
start.bat
硬件要求按 README 说明

仅支持 Windows 10/11;推荐 NVIDIA GPU + CUDA 12.6,RTX 50xx 等 Blackwell 显卡需 CUDA 12.8;也可选 CPU 版 PyTorch 运行。README 未给出具体显存要求。

纯 CPU 可运行需要 CUDA
下载:源码 zip·GitHub Releases(安装包)本站不镜像安装包

项目说明

由 README 自动翻译提炼

Windows 实时音频翻译工具,抓取系统声音和麦克风,经 ASR 后用 LLM 流式翻译并显示在透明悬浮层

抓取系统音频和麦克风,用 Whisper/SenseVoice 做语音识别,再通过 LLM API 流式翻译并实时显示字幕,适合主播、VTuber 和看外语视频时用。

核心能力

  • 用 WASAPI loopback 抓取系统音频,无需改动播放器
  • 32ms 分块配合 Silero VAD 做低延迟语音检测
  • 支持 faster-whisper、SenseVoice、FunASR Nano、Anime-Whisper 多种 ASR 引擎
  • 兼容任意 OpenAI 格式 API,逐字流式输出译文
  • 透明置顶、可点击穿透的悬浮字幕层,内置 14 种配色

容易踩的坑

首次启动会自动下载 Silero VAD 和 SenseVoice 模型(约 1GB),需联网并选好 ModelScope 或 HuggingFace 源;必须自行配置 OpenAI 兼容的翻译 API Base、Key 和模型名才能翻译;Python 需 3.10–3.12,PyTorch 要按显卡选 cu126/cu128/cpu 对应源安装。

内容由模型根据 README 生成,可能不完整或不准确,以官方文档为准。看原文 README

最近发版

5 个版本v2026.08.17.1
  1. v2026.08.17.1最新正式版2026-08-17 · 2026-08-17 02:56 UTC

    更新内容

    • 增量 ASR 的分句库从 PySBD 切换到 yasbd-lib (#37): API 兼容无行为变化, 新增韩语等 17 种语言的原生分句规则 (此前韩语回退英语规则), 长文本分割速度大幅提升

    Changes

    • Incremental ASR sentence segmentation switched from PySBD to yasbd-lib (#37): API-compatible with no behavior change, adds native rules for Korean and 16 more languages (Korean previously fell back to English rules), and is much faster on long text
  2. v2026.08.172026-08-17 · 2026-08-17 02:39 UTC
    查看更新说明

    更新内容

    • 修复 DeepSeek 默认开启思考模式导致翻译返回空、界面显示原文的问题 (#38): 模型编辑对话框新增「禁用思考」风格选择 (自动识别 / DeepSeek·火山方舟·GLM / Qwen·百炼·硅基流动 / vLLM·SGLang 自部署 / OpenAI·Grok reasoning_effort / 不发送), 旧配置自动兼容
    • 修复高 DPI 缩放 (150%+) 下设置窗口超出屏幕、确定/取消按钮点不到的问题 (#39): 设置窗口改为按需滚动, 高度自动限制在屏幕可用范围内
    • 安装与更新不再向系统盘写入下载缓存: 便携版的 uv 缓存和托管 Python、install/update 的 pip 缓存与临时文件全部移入程序目录, 装完自动清理

    Changes

    • Fixed empty translations showing as untranslated same-language text with DeepSeek (#38): the model edit dialog now has a "Disable thinking" style selector (auto-detect / DeepSeek·Volcano Ark·GLM / Qwen·DashScope·SiliconFlow / self-hosted vLLM·SGLang / OpenAI·Grok reasoning_effort / do not send); legacy configs migrate automatically
    • Fixed settings windows overflowing the screen at 150%+ DPI scaling (#39): windows scroll when needed and clamp to the screen's usable height, keeping OK/Cancel reachable
    • Install and update no longer write download caches to the system drive: the portable uv cache and managed Python, plus pip caches and temp files, all live inside the app folder and are cleaned up after setup
  3. v2026.07.112026-07-11 · 2026-07-11 06:45 UTC

    这个版本没有写更新说明。

  4. v2026.06.202026-06-20 · 2026-06-20 14:27 UTC

    这个版本没有写更新说明。

  5. v2026.06.082026-06-08 · 2026-06-08 14:36 UTC

    这个版本没有写更新说明。

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    README 原文

    未翻译

    LiveTranslate

    English | 中文

    Real-time audio translation for Windows. Captures system audio (WASAPI loopback) and optional microphone input, runs ASR, translates via LLM API, and displays results in a transparent overlay.

    Works with any system audio — videos, livestreams, voice chat. No player modifications needed.

    Python 3.10+ Windows License

    Screenshot

    LiveTranslate

    Video

    Install & Demo

    Features

    • Real-time pipeline: System audio → VAD → ASR → LLM translation → overlay
    • Multiple ASR engines: faster-whisper, SenseVoice, FunASR Nano, Anime-Whisper
    • Remote ASR: offload speech recognition to a GPU machine over HTTP — see REMOTE_ASR.md
    • Any OpenAI-compatible API: DeepSeek, Grok, Qwen, GPT, Ollama, vLLM, etc.
    • Streaming translation display: Real-time character-by-character translation output
    • Per-model settings: Streaming, structured output (JSON), context history, disable thinking
    • Microphone mix-in: Optionally mix microphone input with system audio for ASR
    • Low-latency VAD: 32ms chunks + Silero VAD with adaptive silence detection
    • Transparent overlay: Always-on-top, click-through, draggable, 14 color themes
    • CUDA acceleration: GPU-accelerated ASR inference
    • Auto model management: Setup wizard, ModelScope / HuggingFace dual sources
    • Built-in benchmark: Compare translation model speed and quality

    Changelog

    See English Changelog | 中文更新日志

    Requirements

    • OS: Windows 10/11
    • Python: 3.10–3.12 (or use the portable build)
    • GPU (recommended): NVIDIA + CUDA 12.6 (Blackwell GPUs like RTX 50xx require CUDA 12.8)
    • Network: Access to a translation API

    Quick Start

    Portable build (no Python required, recommended for non-developers)

    Download LiveTranslate-portable-*.zip from Releases, unzip, and double-click start.bat. The first run auto-downloads a portable Python 3.12 and installs GPU-aware dependencies — no Python installation needed.

    From source

    git clone https://github.com/TheDeathDragon/LiveTranslate.git
    cd LiveTranslate
    

    Double-click install.bat — the installer will:

    1. Detect Python 3.10–3.12 (auto-install via winget if missing)
    2. Create a virtual environment
    3. Auto-detect NVIDIA GPU and let you choose CUDA / CPU PyTorch
    4. Install all dependencies

    Then double-click start.bat to launch.

    To update, double-click update.bat — it will pull the latest code and update dependencies (auto-installs Git via winget if missing).

    python -m venv .venv
    .venv\Scripts\activate
    
    # PyTorch (choose one)
    pip install torch torchaudio --index-url https://download.pytorch.org/whl/cu126  # CUDA
    pip install torch torchaudio --index-url https://download.pytorch.org/whl/cu128  # CUDA (RTX 50xx)
    pip install torch torchaudio --index-url https://download.pytorch.org/whl/cpu    # CPU only
    
    # Dependencies
    pip install -r requirements.txt
    
    # Launch
    .venv\Scripts\python.exe main.py
    

    First Launch

    1. Setup wizard appears — choose download source (ModelScope / HuggingFace) and cache path
    2. Silero VAD + SenseVoice models download automatically (~1GB)
    3. Main UI appears when ready

    Translation API

    Settings → Translation tab:

    ParameterExample
    API Basehttps://api.deepseek.com/v1
    API KeyYour key
    Modeldeepseek-chat
    Proxynone / system / custom URL

    Architecture

    Audio (WASAPI 32ms) → VAD (Silero) → ASR → LLM Translation → Overlay
             ↑ optional mic mix-in
    
    main.py                 Entry point & pipeline
    ├── audio_capture.py    WASAPI loopback + mic mix-in
    ├── vad_processor.py    Silero VAD
    ├── asr_engine.py       faster-whisper backend
    ├── asr_funasr.py       Unified FunASR model selector backend
    ├── asr_sensevoice.py   SenseVoice backend
    ├── asr_funasr_nano.py  FunASR Nano backend
    ├── asr_anime_whisper.py Anime-Whisper backend (ja anime/galgame)
    ├── asr_remote.py        Remote Whisper client (→ asr_server.py, see REMOTE_ASR.md)
    ├── translator.py       OpenAI-compatible client (streaming, JSON schema, context)
    ├── model_manager.py    Model download & cache
    ├── subtitle_overlay.py PyQt6 overlay
    ├── control_panel.py    Settings UI (7 tabs)
    ├── dialogs.py          Wizard, download & model config dialogs
    └── benchmark.py        Translation benchmark
    

    Acknowledgements

    Star History

    License

    MIT License