C++ library for audio and music analysis, description and synthesis, including Python bindings

A library for audio and music analysis, feature extraction.

List of articles related to deep learning applied to music

FMA: A Dataset For Music Analysis

Omniscient Mozart, being able to transcribe everything in the music, including vocal, drum, chord, beat, instruments, and more.

Audio feature extraction for JavaScript.

Python audio and music signal processing library

CREPE: A Convolutional REpresentation for Pitch Estimation -- pre-trained model (ICASSP 2018)

Instructional notebooks on music information retrieval.

MIDI / symbolic music tokenizers for Deep Learning models 🎶

JavaScript library for music/audio analysis and processing powered by Essentia WebAssembly

Collection of resources on the applications of Large Language Models (LLMs) in Audio AI.

SOME: Singing-Oriented MIDI Extractor.

Music Structure Analysis Framework

A toolkit for symbolic music generation

:sound: spafe: Simplified Python Audio Features Extraction

The official code repo of "HTS-AT: A Hierarchical Token-Semantic Audio Transformer for Sound Classification and Detection"

A C++ Library for Audio Analysis

Olaf: Overly Lightweight Acoustic Fingerprinting is a portable acoustic fingerprinting system.

Tutorial covering Open Source tools for Source Separation.

DALI: a large Dataset of synchronised Audio, LyrIcs and vocal notes.

R wrapper for Spotify's Web API

Code for the paper "LLark: A Multimodal Instruction-Following Language Model for Music" by Josh Gardner, Simon Durand, Daniel Stoller, and Rachel Bittner.

Collection of datasets used for Optical Music Recognition

Metadata, scripts and baselines for the MTG-Jamendo dataset

Official PyTorch implementation of Contrastive Learning of Musical Representations

A python package for handling modern staff notation of music

Fast and simple music and audio analysis using RNN in Python 🕵️‍♀️ 🥁

List of academic resources on Multimodal ML for Music

The Panako acoustic fingerprinting system.