Audiomate is a library for easy access to audio datasets. It provides the datastructures for accessing/loading different datasets in a generic way. This should ease the use of audio datasets for example for machine learning tasks.

Fast and simple music and audio analysis using RNN in Python 🕵️‍♀️ 🥁 - dodiku/AudioOwl: Fast and simple music and audio analysis using RNN in Python 🕵️‍♀️ 🥁

A python package to parse and process the demixing secrets dataset (DSD) as part of the MUS task of the Signal Separation Evaluation Campaign (SISEC)

Open-source library and tools for audio and music analysis, description and synthesis

mirdata is an open-source Python library that provides tools for working with common Music Information Retrieval (MIR) datasets, including tools for: downloading datasets to a common location and format validating that the files for a dataset are all present loading annotation files to a common format, consistent with mir_eval parsing track level metadata for detailed evaluations.

MSAF is a python package for the analysis of music structural segmentation algorithms. It includes a set of features, algorithms, evaluation metrics, and datasets to experiment with.

Mutagen is a Python module to handle audio metadata. It supports ASF, FLAC, MP4, Monkey’s Audio, MP3, Musepack, Ogg Opus, Ogg FLAC, Ogg Speex, Ogg Theora, Ogg Vorbis, True Audio, WavPack, OptimFROG, and AIFF audio files. All versions of ID3v2 are supported, and all standard ID3v2.4 frames are parsed. It can read Xing headers to accurately calculate the bitrate and length of MP3s. ID3 and APEv2 tags can be edited regardless of audio format. It can also manipulate Ogg streams on an individual packet/page level.

🎛 🔊 Documentation for Pedalboard: A Python library for working with audio.

SuperKogito/Spafe 0.3.2 documentation

Torchaudio 2.1.2 documentation

Librosa : audio and music processing in Python

AudioFlux 0.1.2 documentation