sergree/matchering
Matchering
Matchering is an audio mastering tool and Python library designed to match the frequency balance and loudness of a target track to a specific reference track. It functions as a reference-based mastering system that aligns a target signal's spectral envelope, RMS, and peak amplitude with those of a chosen reference file.
The project utilizes a multi-stage processing pipeline featuring an FFT spectral matching engine to adjust frequency response. It ensures output quality through the use of a brickwall limiter to prevent signal clipping while preserving the original waveform shape.
The tool provides a flexible interface available as a programmable Python module, a command-line tool for batch processing, and a containerized web service deployable via Docker. It includes an input validation layer to detect clipping, lossy compression, and sample rate mismatches, while automatically handling mono-to-stereo conversion and audio resampling.
Features
- Reference-Based Audio Mastering - Matches the frequency balance and loudness of a target track to a specific reference track through a multi-stage pipeline.
- Reference-Based Mastering - Adjusts an audio file's frequency balance and loudness to match the sonic characteristics of a chosen reference track.
- Multi-Stage Pipeline Processing - Implements a multi-stage pipeline to chain sequential audio transformations for mastering.
- FFT Spectral Processing - Utilizes Fast Fourier Transforms to match the frequency balance and spectral envelope of a target track to a reference.
- Audio Mastering Tools - Provides a tool to match the frequency balance and loudness of a target track to a reference.
- Audio Processing - Provides a Python library and CLI for executing professional audio mastering tasks.
- Audio Reference Matching - Matches a target track's frequency balance and loudness to a reference for automated mastering.
- Audio Source Matching - Aligns a target track to a reference by matching loudness, frequency response, peak amplitude, and stereo width.
- Audio Processing Pipelines - Transforms audio through a sequential pipeline of frequency matching, loudness normalization, and peak limiting.
- Audio Processing Pipelines - Implements a multi-stage processing pipeline that applies EQ, compression, limiting, and stereo width matching.
- Peak Limiters - Implements a brickwall limiter to prevent clipping while preserving the original waveform shape.
- Python Audio Manipulation Libraries - Implements a Python library for integrating automated audio mastering and peak limiting into custom software.
- Audio Signal Quality Validators - Provides a validation layer to detect clipping, lossy compression, and sample rate mismatches in input audio files.
- Audio Batch Utilities - Processes multiple audio files through a mastering pipeline using a command-line interface.
- Audio Command-Line Tools - Offers a command-line interface for batch processing audio mastering tasks.
- Library and CLI Interfaces - Offers both a programmable Python module and a standalone command-line tool.
- Audio File Analyzers - Checks audio files for stream errors, length limits, and channel counts before processing.
- Dockerized Services - Provides the mastering pipeline as a ready-to-run Dockerized service accessible via a web interface.
- Audio Processing Services - Deploys an audio mastering service in a Docker container with a web interface.
- Audio Mastering Web Interfaces - Ships a Docker-packaged mastering service with a web interface for reference-based processing.
- Audio Processing Services - Provides a containerized web service to perform audio mastering via a browser interface.
- Containerized - Provides a containerized web application for performing reference-based audio mastering.
- Sample Rate Conversion - Adjusts the sample rate of input files to match the internal processing rate for technical compatibility.
- Audio Quality Evaluation Tools - Validates input audio files for clipping, lossy compression, and sample rate mismatches before processing.
- Audio Quality Validation - Validates audio files for stream errors, clipping, and sample rate mismatches before processing.
- Input Validation - Includes a validation layer to check audio streams for clipping and compression errors.
- Containerized Web Interfaces - Exposes the audio processing pipeline via a browser-based service launched from a Docker container.
- Automation - Containerized web application for automated music mastering.
- Automation Tools - Listed in the “Automation Tools” section of the Awesome Selfhosted awesome list.
- Audio Tools - Containerized application for automated reference audio mastering.
- Digital Signal Processing - Automated reference-based audio mastering.
- Audio and Video Processing - Automates audio mastering using reference tracks.
- Audio Processing - Library for audio mastering.
- Audio Video Processing - Listed in the “Audio Video Processing” section of the Awesome Python awesome list.
Star history
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