Open Source Audio Processing Projects
Audio processing uses software to capture, transform, analyze, and generate sound. It supports tasks such as filtering noise, adjusting effects, converting formats, extracting features, and preparing speech or music for playback, transcription, and machine learning. These tools help make audio clearer, more accessible, and suitable for different applications and devices.
Open source options include audio libraries, signal analysis frameworks, effect processors, speech tools, and applications for editing or streaming sound. When choosing one, consider its license, maintenance activity, documentation, supported formats, performance requirements, and compatibility with your existing workflow. These tools are useful to developers, researchers, musicians, media teams, and anyone building audio features or processing recordings.
4 repositories · updated October 3, 2026
TimeSide: Process and Analyze Audio at Scale
TimeSide is a Python framework and server for analyzing, transforming, visualizing, and streaming audio and video. It suits research teams and developers building audio workflows, archives, or web services that need extensible processing across large collections.
AudioSep: Separate Sounds from Natural-Language Descriptions
AudioSep is a Python foundation model for separating sounds from audio based on natural-language descriptions. It supports open-domain tasks such as isolating events, instruments, or speech, with inference, fine-tuning, and evaluation workflows.
fast-music-remover: Remove Music and Noise from Media Audio
Fast Music Remover processes audio from uploaded files or internet media to reduce background music and noise. It combines a C++ audio processor using DeepFilterNet with a Flask web interface, and can be run in Docker or set up manually.
pedalboard: Process Audio and Apply Effects in Python
Pedalboard is a Python library for reading, transforming, and rendering audio, with built-in effects and support for VST3 and Audio Unit plugins. It suits audio developers and machine-learning workflows that need programmable audio processing.