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Decision brief
WhisperJAV employs Qwen3-ASR and Whisper for automatic speech recognition tailored specifically to JAV content, offering robust noise handling.
Good fit when
- When you need specialized noise-robust subtitling specifically designed for JAV content.
- For users who require the integration of local language models (LLMs) with ASR functionalities.
Avoid when
- Avoid if you are working on non-JAV content which does not benefit from specific noise handling optimized for JAV.
- Not suitable if your project is solely focused on real-time ASR without the need for extensive offline processing and noise correction provided by WhisperJAV.
- Pricing:
- freemium - The tool itself is free under MIT license, but users may incur costs related to required hardware, especially if using it extensively with high-performance GPU setups.
- Requirements:
- Min 8 GB RAM; Operating systems supported are Windows 10+, macOS 11+, and Ubuntu 20.04+.; Requires Python version between 3.10 and 3.12; recommended Python versions vary by platform but generally aim for the latest within this range.
Observed Jul 17, 2026 · Source: enrich:decision_facts
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Maintenance and security
Full trust report- Maintenance
- Steady (81d since push)
- As of 3w
- Provenance
- Not a fork · Personal account
- As of 3w
- Security (OSV)
- No lockfile
- As of 1mo
Public GitHub metadata and optional OSV scans. Signals, not a guarantee. Trust methodology.
Install
pip install WhisperJAVSimilar tools
Same-category neighbours. No typed graph edges are catalogued for this tool yet.
Evidence and technical details
Sourced facts, taxonomy, compatibility claims, README excerpt, and machine-readable endpoints.
Overview
WhisperJAV uses Qwen3-ASR, local LLMs, and Whisper for noise-robust subtitling of JAV content.
Capability facts
- CLI
- CLI entrypoint
Source: pyproject.toml:[project.scripts] · Jul 30, 2026
- Languages
- python
Source: github.language+pyproject.toml · Jul 30, 2026
Categories
Compatibility
Sourced claims from the README excerpt - not unsourced marketing copy.
Source: README excerpt (regex_v1, Jul 30, 2026)
For people who manage their own Python environments.Source link
Tags
README
Installation
Upgrading? Run
whisperjav-upgrade(works on Windows, Linux, and macOS). For code-only updates:whisperjav-upgrade --wheel-only. See the Upgrade Guide for details.
Which Installation Path Should I Follow?
| Your Situation | Go To |
|---|---|
| New user on Windows wanting GUI | Windows Standalone Installer |
| Developer on Windows | Windows Source Install |
| macOS user | macOS (Apple Silicon) |
| Linux user | Linux |
| Colab or Kaggle | Cloud Notebooks |
| Developer or expert wanting pip | Expert Installation |
Windows Source Install
For people who manage their own Python environments.
Prerequisites: Python 3.10-3.12, Git, FFmpeg in PATH.
git clone https://github.com/meizhong986/whisperjav.git
cd whisperjav
:: Full automated install (auto-detects GPU)
installer\install_windows.bat
:: Or with options:
installer\install_windows.bat --cpu-only :: Force CPU
installer\install_windows.bat --cuda118 :: Force CUDA 11.8
installer\install_windows.bat --cuda128 :: Force CUDA 12.8
installer\install_windows.bat --local-llm :: Include local LLM translation
The installer runs in 5 phases: PyTorch first (with GPU detection), then scientific stack, Whisper packages, audio/CLI tools, and optional extras. This order matters — PyTorch must be installed before anything that depends on it, or you end up with CPU-only wheels.
For the full walkthrough, see docs/en/guides/installation_windows_python.md.
Recommended: use the install script
chmod +x installer/install_linux.sh ./installer/install_linux.sh
Expert Installation
For users comfortable with Python package management. Choose the components you need.
Modular Installation
WhisperJAV supports modular extras. Install only what you need:
---
# Install in editable mode with dev dependencies
pip install -e ".[dev]"
---
### System Requirements
| Requirement | Minimum | Recommended |
|-------------|---------|-------------|
| **OS** | Windows 10, macOS 11, Ubuntu 20.04 | Windows 11, macOS 14, Ubuntu 22.04 |
| **Python** | 3.10 | 3.11 |
| **RAM** | 8 GB | 16 GB |
| **Disk** | 8 GB | 15 GB (with models) |
| **GPU** | None (CPU works) | NVIDIA RTX 2060+ or Apple Silicon |
**GPU Support:**
- NVIDIA: CUDA 11.8 or 12.8 (Windows, Linux)
- Apple Silicon: MPS acceleration for Whisper (M1/M2/M3/M4/M5). Qwen pipeline is CPU-only on Mac for now.
- AMD ROCm: Experimental (Linux only)
- CPU fallback: Works on all platforms, 5-10x slower
**Processing Time Estimates (per hour of video):**
| Hardware | Time |
|----------|------|
| NVIDIA RTX GPU | 5-10 minutes |
| Apple Silicon | 8-15 minutes |
| CPU | 30-60 minutes |
---
---
## License
MIT License. See [LICENSE](LICENSE) file.
---
For agents
This page has a .md twin and JSON over the API.