An open-source, end-to-end neural voice conversion & model training ecosystem built for ultra-low latency, quality, and cross-platform flexibility.

⚡ The Beatrice V2 Pipeline

  ┌───────────────────────────┐      ┌───────────────────────────┐      ┌───────────────────────────┐
  │  1. Dataset Web UI        │ ───► │  2. Model Trainer         │ ───► │  3. Real-Time Changer     │
  │  • Audio Slicing & Clean  │      │  • macOS (MPS) & Win (CUDA│      │  • Ultra-low latency VST  │
  │  • Quality Validation     │      │  • Free Google Colab      │      │  • Live Discord/OBS stream│
  └───────────────────────────┘      └───────────────────────────┘      └───────────────────────────┘

📦 Repositories & Modules Directory

Module / Repository	Platform Support	Features & Description
🎙️ Beatrice-voicechanger-macos		Real-time Beatrice voice changer for macOS featuring Metal/MPS hardware acceleration and ultra-low latency.
🎙️ Beatrice-voicechanger-windows		Fast, lightweight, low-latency live voice conversion running locally with GPU acceleration on Windows.
🧠 Beatrice-trainer-macos		Train Beatrice voice models locally on macOS with a clean desktop UI and optimized Apple Silicon pipeline.
🧠 Beatrice-trainer-windows		Streamlined Windows trainer for custom voice models with complete offline support and efficient training.
☁️ Beatrice-colab		Cloud training notebooks for Google Colab & Kaggle. Train models on free T4/A100 GPUs without local hardware.
📂 Beatrice-dataset-webui-macos		Web-based dataset creator for macOS. Automatically slice long audio files, clean noise, and format training sets.
📂 Beatrice-dataset-webui-windows		Intuitive web UI for Windows to build, process, and package voice datasets for Beatrice model training.

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🛠️ End-to-End Workflow

Step 1: Dataset Preparation (Web UI)

1. Launch Beatrice-dataset-webui-macos or Beatrice-dataset-webui-windows depending on your OS.
2. Load your raw voice recordings into the interface.
3. Automatically slice long files into clean audio segments, validate transcriptions/silence, and export a ready-to-train dataset zip.

Step 2: Model Training

• macOS (Local): Use Beatrice-trainer-macos for native Apple Silicon MPS training.
• Windows (Local): Use Beatrice-trainer-windows for CUDA / DirectML hardware acceleration.
• Cloud (Free GPU): Launch Beatrice-colab on Google Colab or Kaggle to train without needing a high-end local GPU.

Step 3: Real-Time Live Inference

1. Export your trained voice model.
2. Open Beatrice-voicechanger-macos or Beatrice-voicechanger-windows.
3. Route your physical microphone into the voice changer and output to a virtual audio channel (e.g. VB-Cable / BlackHole).
4. Use transformed voices live in Discord, OBS, games, or live streaming apps!

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_{Built with ❤️ by the Project Beatrice V2 Team • Released under the MIT License}