AudioEnhancer

A production-grade Python audio enhancement toolkit.

Features

• Noise Removal: Spectral gating, impulse noise removal, and more.
• Audio Normalization: Peak, RMS, and LUFS (EBU R128).
• Format Conversion: Convert between various audio formats like WAV, MP3, FLAC, etc.
• Advanced Architecture: Built with OOP and common software design patterns.

Prerequisites

This project requires FFmpeg to be installed and available in your system's PATH.

Installation

1. Clone the repository:

   git clone https://github.com/CodeWithBotinaOficial/audio_enhancer.git
   cd audio_enhancer

2. Create a virtual environment and install dependencies:

   python -m venv venv
   source venv/bin/activate  # On Windows use `venv\Scripts\activate`
   pip install -r requirements.txt

Usage

Command-Line Interface (CLI)

The CLI provides a quick way to process audio files.

python cli.py process-file examples/sample_audio/input.wav examples/output/output.mp3 --noise-profile spectral_gate --normalize lufs --lufs -16.0

Library Usage

The project can be used as a Python library by importing the AudioEnhancer facade.

from audio_enhancer.enhancer import AudioEnhancer
from audio_enhancer.normalization.lufs import LufsNormalizer
from audio_enhancer.noise_reduction.spectral_gating import SpectralGatingNoiseReducer

def main():
    # Create an enhancer instance
    enhancer = AudioEnhancer.get_instance()

    # Load an audio file
    audio = enhancer.load_audio("examples/sample_audio/input.wav")

    # Create a processing pipeline
    pipeline = (
        enhancer.get_builder()
        .add_step(SpectralGatingNoiseReducer())
        .add_step(LufsNormalizer(-16.0))
        .build()
    )

    # Apply the pipeline
    enhanced_audio = pipeline.process(audio)

    # Export the result
    enhancer.export_audio(enhanced_audio, "examples/output/enhanced_audio.flac", "flac")
    print("Audio enhancement complete.")

if __name__ == "__main__":
    main()

Design Patterns

This project serves as a practical example of various software design patterns:

• Facade: AudioEnhancer class provides a simple, high-level interface.
• Strategy: Different normalization and noise reduction algorithms are implemented as strategies.
• Builder: PipelineBuilder constructs complex processing pipelines step-by-step.
• Singleton: The Logger and AudioEnhancer use the Singleton pattern.
• Factory Method: Used to create different audio processors.
• ... and many more. See the audio_enhancer/patterns/ directory for detailed examples.