Dataset Viewer

The dataset viewer is not available because its heuristics could not detect any supported data files. You can try uploading some data files, or configuring the data files location manually.

YAML Metadata Warning:empty or missing yaml metadata in repo card

Check out the documentation for more information.

LiveTrans

English | 中文

Real-time audio translation tool for Windows. Captures system audio via WASAPI loopback, runs speech recognition (ASR), translates through LLM APIs, and displays results in a transparent overlay window.

Perfect for watching foreign-language videos, livestreams, and meetings — no player modifications needed, works with any system audio.

Python 3.10+ Windows License

Features

  • Real-time translation: System audio → ASR → LLM translation → subtitle overlay, fully automatic
  • Multiple ASR engines: faster-whisper, FunASR SenseVoice (optimized for Japanese), FunASR Nano
  • Flexible translation backend: Compatible with any OpenAI-format API (DeepSeek, Grok, Qwen, GPT, etc.)
  • Low-latency VAD: 32ms audio chunks + Silero VAD with adaptive silence detection
  • Transparent overlay: Always-on-top, click-through, draggable — doesn't interfere with your workflow
  • CUDA acceleration: GPU-accelerated ASR inference
  • Automatic model management: First-launch setup wizard, supports ModelScope / HuggingFace dual sources
  • Translation benchmark: Built-in benchmark tool for comparing model performance

Screenshots

English → Chinese (Twitch livestream)

English to Chinese

Japanese → Chinese (Japanese livestream)

Japanese to Chinese

Requirements

  • OS: Windows 10/11
  • Python: 3.10+
  • GPU (recommended): NVIDIA GPU with CUDA 12.6 (for ASR acceleration)
  • Network: Access to a translation API (DeepSeek, OpenAI, etc.)

Installation

1. Clone the repository

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

2. Create a virtual environment

python -m venv .venv
.venv\Scripts\activate

3. Install PyTorch (with CUDA)

Choose the install command based on your CUDA version. See PyTorch official site:

# CUDA 12.6 (recommended)
pip install torch torchaudio --index-url https://download.pytorch.org/whl/cu126

# CPU only (no NVIDIA GPU)
pip install torch torchaudio --index-url https://download.pytorch.org/whl/cpu

4. Install remaining dependencies

pip install -r requirements.txt
pip install funasr --no-deps

Note: FunASR is installed with --no-deps because its dependency editdistance requires a C++ compiler. The pure-Python alternative editdistance-s is included in requirements.txt as a drop-in replacement.

5. Launch

.venv\Scripts\python.exe main.py

Or double-click start.bat.

First Launch

  1. A setup wizard will appear on first launch — choose your model download source (ModelScope for China, HuggingFace for international) and model cache path
  2. Silero VAD and SenseVoice ASR models will be downloaded automatically (~1GB)
  3. The main UI appears once downloads complete

Configuring the Translation API

Click Settings on the overlay → Translation tab:

Parameter Description
API Base API endpoint, e.g. https://api.deepseek.com/v1
API Key Your API key
Model Model name, e.g. deepseek-chat
Proxy none (direct) / system (system proxy) / custom proxy URL

Works with any OpenAI-compatible API, including:

Usage

  1. Play a video or livestream with foreign-language audio
  2. Launch LiveTrans — the overlay appears automatically
  3. Recognized text and translations are displayed in real time

Overlay Controls

  • Pause/Resume: Pause or resume translation
  • Clear: Clear current subtitles
  • Click-through: Mouse clicks pass through the subtitle window
  • Always on top: Keep overlay above all windows
  • Auto-scroll: Automatically scroll to the latest subtitle
  • Model selector: Switch between configured translation models
  • Target language: Change the translation target language

Settings Panel

Open via the Settings button on the overlay or the system tray menu:

  • VAD/ASR: ASR engine selection, VAD mode, sensitivity parameters
  • Translation: API configuration, system prompt, multi-model management
  • Benchmark: Translation speed and quality benchmarks
  • Cache: Model cache path management

Architecture

Audio (WASAPI 32ms) → VAD (Silero) → ASR (Whisper/SenseVoice/Nano) → LLM Translation → Overlay
main.py                 Entry point & pipeline orchestration
├── audio_capture.py    WASAPI loopback audio capture
├── vad_processor.py    Silero VAD speech detection
├── asr_engine.py       faster-whisper ASR backend
├── asr_sensevoice.py   FunASR SenseVoice backend
├── asr_funasr_nano.py  FunASR Nano backend
├── translator.py       OpenAI-compatible translation client
├── model_manager.py    Model detection, download & cache management
├── subtitle_overlay.py PyQt6 transparent overlay window
├── control_panel.py    Settings panel UI
├── dialogs.py          Setup wizard & model download dialogs
├── log_window.py       Real-time log viewer
├── benchmark.py        Translation benchmark
└── config.yaml         Default configuration

Known Limitations

  • Windows only (depends on WASAPI loopback)
  • ASR model first load takes a few seconds (GPU) to tens of seconds (CPU)
  • Translation quality depends on the LLM API used
  • Recognition degrades in noisy environments or with overlapping speakers

License

MIT License

Downloads last month
56