A privacy-focused, offline text-to-speech engine using Qwen3-TTS models for realistic voice cloning and high-fidelity speech synthesis.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install local-tts
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install local-tts using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Local TTS with Qwen3-TTS?
Local-tts is a high-performance text-to-speech solution designed for users who prioritize privacy and performance. By leveraging Qwen3-TTS models, this tool ensures that your data never leaves your machine, making it a perfect fit for Openclaw Skills users who require 100% on-device processing. It supports a wide range of platforms, optimized specifically for Apple Silicon via mlx_audio and for Linux/Windows using standard CUDA backends.
The skill provides a flexible ecosystem for speech synthesis, including preset natural voices, text-based voice design, and high-fidelity voice cloning. Whether you are building local voice assistants or generating audio for long-form content, this implementation delivers natural, human-like speech without the need for external API keys or internet connectivity. Using this within the Openclaw Skills framework allows for seamless local integration of advanced speech capabilities.
Local TTS with Qwen3-TTS Use Cases
- Generating professional voiceovers for videos without cloud dependency.
- Building privacy-compliant healthcare or legal applications that process sensitive data locally.
- Creating custom voice clones for personalized AI assistants using Openclaw Skills.
- Producing long-form audio content from text files while offline.
- Real-time speech synthesis for interactive local applications on macOS and Linux.
How Local TTS with Qwen3-TTS Works
- The user selects a Qwen3-TTS model variant based on their hardware (Apple Silicon or NVIDIA GPU) and specific needs such as Preset, Design, or Cloning.
- Text input is processed locally through the chosen model backend, such as mlx_audio for optimized macOS performance.
- The system applies optional parameters like speed, pitch, and emotional instructions to the synthesis engine.
- High-quality audio is generated in real-time and saved to a local file, ensuring zero data transmission to external servers as expected from Openclaw Skills.
Local TTS with Qwen3-TTS Setup
For macOS (Apple Silicon):
pip install mlx-audio
brew install ffmpeg
For Linux/Windows (CUDA):
pip install qwen-tts
To run a basic synthesis using Openclaw Skills architecture:
python -m mlx_audio.tts.generate --text "Hello world" --model mlx-community/Qwen3-TTS-12Hz-1.7B-CustomVoice-8bit --voice Serena
Local TTS with Qwen3-TTS Data Schema & Taxonomy
| Component | Description | Data Format |
|---|---|---|
| Output Audio | Synthesized speech results | .wav |
| Reference Audio | Input file for voice cloning | .wav, .mp3 |
| Model Weights | Local Qwen3-TTS weights | SafeTensors |
| Parameters | CLI arguments for speed, pitch, and voice | String/Float |
Local TTS with Qwen3-TTS Advanced Features
- Text-based VoiceDesign for creating unique synthetic voices from natural language descriptions.
- Zero-shot voice cloning capabilities using the Base model and a short reference audio clip.
- Optimized long-text generation with automatic segment joining and token management.
- Support for style and emotion control (e.g., excited, empathetic) when using CustomVoice models.
- Native optimization for Apple Silicon and CUDA-enabled Linux environments within Openclaw Skills.
SKILL.md
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