VoxCPMANE
December 14, 2025 ยท View on GitHub
Try the beta with the VoxCPM1.5 model !!
uv pip install -U --pre voxcpmane
VoxCPM TTS model with Apple Neural Engine (ANE) backend server. CoreML models available in Huggingface repository.
- ๐ค Voice Cloning: Support for custom voice prompts and cached voices
- ๐ก Streaming Support: Real-time audio streaming for low latency
- ๐ง Server-side Playback: Direct audio playback on the server
- ๐ Web Interface: Interactive playground for testing
Voice Cloning
https://github.com/user-attachments/assets/02ffa400-b2fd-422e-a3ad-a0ea232a55aa
Included Voices Listen samples
https://github.com/user-attachments/assets/28880ed2-2e21-4eb4-b0ce-18a100403e87
Installation
Prerequisites
- macOS with Apple Silicon for ANE acceleration
- Python 3.9-3.12
- uv package manager (recommended)
pydubrequired for audio formats other thanwavin/speechendpoint
Install with pip or uv
uv pip install voxcpmane
pip install voxcpmane
The server will start on http://localhost:8000 by default. You can access the web playground at the root URL.
Configuration
Command Line Options
uv run voxcpmane-server --help
--host: Host to bind the server to (default:0.0.0.0)--port: Port to run the server on (default:8000)--cache-dir: Directory for custom voice caches (default:~/.cache/ane_tts)
Custom Voices
You can create reusable cached voices in two ways:
- Via the Web Playground/API: Use the "Create Voice" tab or
POST /v1/voicesendpoint. - Startup Compilation: Place pairs of audio files (e.g.,
.wav,.mp3) and transcriptions (.txt) in the custom cache directory. The server will automatically compile them into voice caches (.npy) on startup.
Example:
If you place myvoice.mp3 and myvoice.txt in the cache directory, the server will generate myvoice.npy on start, making "myvoice" available for generation.
API Reference
The full API documentation is available in docs/API.md.
Changelog
Version 0.0.3
- Added support for creation of custom voices
Roadmap
- Automatic prompt caching
- Chunked long audio generation
- Custom voices
Acknowledgments
- VoxCPM - Original TTS model