README_Enhanced.md

# 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

ash git clone https://github.com/SociallyIneptWeeb/AICoverGen.git cd AICoverGen

Step 2: Create Virtual Environment

`ash

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)

ash pip install -r requirements.txt

Option B: Manual Installation

`ash

Core dependencies

pip install gradio==3.50.2 pip install librosa==0.9.1 pip install numpy==1.23.5 pip install scipy==1.11.1 pip install soundfile==0.12.1 pip install pedalboard==0.7.7 pip install pydub==0.25.1 pip install fairseq==0.12.2 pip install faiss-cpu==1.7.3 pip install pyworld==0.3.4 pip install praat-parselmouth>=0.4.2 pip install ffmpeg-python>=0.2.0 pip install tqdm==4.65.0 pip install yt-dlp>=2025.9.23 pip install sox==1.4.1

AI Audio Enhancement dependencies

pip install noisereduce==3.0.3 pip install 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

ash python src/download_models.py

Step 5: Verify Installation

ash python src/audio_enhancer.py

Usage

Quick Start

1. Start the Web UI: ash python src/webui.py

2. Open your browser and go to http://127.0.0.1:7860

3. Upload a song (YouTube URL or audio file)

4. Select a voice model from the dropdown

5. 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%)

6. Click Generate and enjoy your enhanced AI cover!

Troubleshooting

Common Issues

CUDA Not Detected

`ash

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

`ash

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 machine learning to identify and remove background noise
• Preserves vocal clarity while eliminating artifacts
• Adjustable strength from 0-100%

Professional EQ

• Balanced: Gentle mid boost for overall clarity
• Vocal Boost: Emphasizes 800-3000 Hz range for vocals
• Bass Boost: Enhances 60-250 Hz for low-end presence
• Treble Boost: Brightens 4-16 kHz for crispness
• Flat: Minimal processing with high-pass filter

Dynamic Range Compression

• Improves loudness consistency
• Reduces dynamic range for better streaming
• Configurable ratio from 1-10

Harmonic Enhancement

• Adds warmth and richness to vocals
• Uses soft saturation for natural harmonics
• Enhances perceived quality

Stereo Widening

• Improves spatial imaging for stereo tracks
• Enhances left-right separation
• Creates more immersive listening 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.

Development Setup

ash git clone https://github.com/SociallyIneptWeeb/AICoverGen.git cd AICoverGen pip install -r requirements.txt pip install -r requirements-dev.txt # If available

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

Support

• Issues: GitHub Issues
• Discussions: GitHub Discussions
• Documentation: Wiki

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**Happy Creating! **

Create amazing AI voice covers with professional audio enhancement!