--- title: Rvc Effects sdk: gradio emoji: 🔥 colorFrom: indigo colorTo: purple --- # AICoverGen An autonomous pipeline to create covers with any RVC v2 trained AI voice from YouTube videos or a local audio file. For developers who may want to add a singing functionality into their AI assistant/chatbot/vtuber, or for people who want to hear their favourite characters sing their favourite song. image # AICoverGen Enhanced **AI-Powered Voice Cover Generation with Advanced Audio Enhancement** AICoverGen Enhanced is a powerful tool for creating AI voice covers with professional-grade audio enhancement features. This enhanced version includes advanced AI audio processing, EQ controls, dynamic range compression, and much more! --- ## ✨ New Features ### Advanced Audio Enhancement - **AI Noise Reduction** – Remove background noise and artifacts - **Professional EQ** – 5 EQ types: Balanced, Vocal Boost, Bass Boost, Treble Boost, Flat - **Dynamic Range Compression** – Improve loudness and consistency - **Harmonic Enhancement** – Add richness and warmth to vocals - **Stereo Widening** – Enhance spatial imaging for stereo tracks - **Reverb Control** – Add depth and professional polish - **Gain Control** – Fine-tune volume (-20 to +20 dB) ### Enhancement Types - **Full** – Balanced enhancement with all features - **Light** – Subtle improvements for natural sound - **Aggressive** – Maximum enhancement for impact - **Custom** – Use your specific settings --- ## 🖥️ System Requirements ### Minimum Requirements - **OS:** Windows 10/11, Linux, or macOS - **Python:** 3.9+ (3.10+ recommended) - **RAM:** 8GB minimum, 16GB recommended - **Storage:** 10GB free space - **GPU:** NVIDIA GPU with CUDA support (recommended) ### Recommended Setup - **OS:** Windows 11 or Ubuntu 20.04+ - **Python:** 3.10 or 3.11 - **RAM:** 16GB or more - **GPU:** NVIDIA RTX 3060 or better - **CUDA:** 11.8 or 12.0+ - **cuDNN:** 8.6 or 9.0+ --- ## ⚙️ Installation Guide ### Step 1: Clone the Repository ```bash git clone https://github.com/SociallyIneptWeeb/AICoverGen.git cd AICoverGen ``` ### Step 2: Create Virtual Environment ```bash # Windows python -m venv AICoverGen AICoverGen\Scripts\activate # Linux/macOS python3 -m venv AICoverGen source AICoverGen/bin/activate ``` ### Step 3: Install Dependencies #### Option A: Automatic Installation (Recommended) ```bash pip install -r requirements.txt ``` #### Option B: Manual Installation ```bash # Core dependencies pip install gradio==3.50.2 librosa==0.9.1 numpy==1.23.5 scipy==1.11.1 soundfile==0.12.1 pip install pedalboard==0.7.7 pydub==0.25.1 fairseq==0.12.2 faiss-cpu==1.7.3 pyworld==0.3.4 pip install praat-parselmouth>=0.4.2 ffmpeg-python>=0.2.0 tqdm==4.65.0 yt-dlp>=2025.9.23 sox==1.4.1 # AI Audio Enhancement dependencies pip install noisereduce==3.0.3 scikit-learn==1.6.1 # PyTorch with CUDA support pip install torch==2.0.1+cu118 --find-links https://download.pytorch.org/whl/torch_stable.html pip install torchcrepe==0.0.20 # ONNX Runtime with CUDA support pip install onnxruntime-gpu==1.18.0 ``` ### Step 4: Download Models ```bash python src/download_models.py ``` ### Step 5: Verify Installation ```bash python src/audio_enhancer.py ``` --- ## 🚀 Usage ### Quick Start ```bash python src/webui.py ``` Then open your browser and go to: [http://127.0.0.1:7860](http://127.0.0.1:7860) 1. Upload a song (YouTube URL or audio file) 2. Select a voice model from the dropdown 3. Configure audio enhancement: - Expand "AI Audio Enhancement" section - Choose enhancement type (Full/Light/Aggressive/Custom) - Adjust EQ type (Balanced/Vocal Boost/Bass Boost/Treble Boost/Flat) - Set noise reduction strength (0–100%) - Adjust gain (-20 to +20 dB) - Set compression ratio (1–10) - Add reverb amount (0–100%) 4. Click **Generate** and enjoy your enhanced AI cover! --- ## 🛠️ Troubleshooting ### CUDA Not Detected ```bash # Check CUDA installation nvidia-smi # Verify PyTorch CUDA support python -c "import torch; print(torch.cuda.is_available())" # Check ONNX Runtime CUDA python -c "import onnxruntime as ort; print('CUDA' in ort.get_available_providers())" ``` ### Audio Enhancement Errors ```bash # Test audio enhancer python src/audio_enhancer.py # Check dependencies pip list | grep -E "(noisereduce|scikit-learn|pedalboard)" ``` ### Memory Issues - Reduce batch size in settings - Use CPU-only mode for ONNX Runtime - Close other applications to free RAM --- ## 📂 Project Structure ``` AICoverGen_Enhanced/ ├── src/ │ ├── webui.py # Main web interface │ ├── main.py # Core pipeline with audio enhancement │ ├── audio_enhancer.py # AI audio enhancement module │ ├── rvc.py # RVC voice conversion │ ├── mdx.py # Audio separation ├── rvc_models/ # Voice models ├── mdxnet_models/ # Audio separation models ├── song_output/ # Generated covers ├── requirements.txt # Dependencies ├── README_Enhanced.md # This file ``` --- ## 🎚️ Audio Enhancement Features ### AI Noise Reduction - Uses ML to identify and remove background noise - Preserves vocal clarity while eliminating artifacts - Adjustable strength (0–100%) ### Professional EQ - **Balanced**: Gentle mid boost for clarity - **Vocal Boost**: Emphasizes 800–3000 Hz range - **Bass Boost**: Enhances 60–250 Hz - **Treble Boost**: Brightens 4–16 kHz - **Flat**: Minimal processing with high-pass filter ### Dynamic Range Compression - Improves loudness consistency - Reduces dynamic range for streaming - Configurable ratio (1–10) ### Harmonic Enhancement - Adds warmth and richness - Uses soft saturation for natural harmonics ### Stereo Widening - Improves spatial imaging - Enhances left-right separation - Creates immersive experience ### Reverb Control - Adds subtle depth and space - Professional room simulation - Configurable wet/dry mix --- ## 🤝 Contributing We welcome contributions! Please see our **Contributing Guidelines** for details. --- ## ⚖️ License This project is licensed under the **MIT License** – see the LICENSE file for details. --- ## 🙏 Acknowledgments - Original AICoverGen by **SociallyIneptWeeb** - RVC (Retrieval-based Voice Conversion) framework - MDXNet for audio separation - All the amazing open-source audio processing libraries