Genre Classification using Convolutional Neural Networks

Generative models for conditional audio generation - Stability-AI/stable-audio-tools

Generate vector embeddings for music

Full-stack song recognition application with audio fingerprinting and hum to search (QbSH) modules

Extracts metadata music metadata found in audio files

Extension of the music21 library for working with music chords encoded according to the Harte Notation.

Export your Deezer playlists in a breath

Examples of apps built with Nendo, the AI Audio Tool Suite

Endless Semi-Generative Performance Piano Music Maker

Docs, patches, scripts, tools & utilities mainly related to VCV Rack, Wotjia and Monome Norns. Shield

DJ tool for suggesting tracks for harmonic mixing with Traktor Pro (from Native Instruments)

Detecting segments belonging to which song in database, and return Nil if does not exist in a database.

Data pipeline and training pipeline for 🎵 music genre classification from FMA dataset

Cross-platform music production software

Cover Song Identification with Keras

Convolutional Neural Network for auto-tagging of audio clips on MagnaTagATune dataset

Converting music to a ML friendly format and analyzing it.

Convert any music library into a music production sample-library with ML

Content-based Music Genre Classification

Connecting Spotify songs to MusicBrainz to find new music based on song titles

Combine any music sources into a single library. It's your music. Play it your way.

Collection of userscripts for MusicBrainz, by various authors

Collection of datasets used for Optical Music Recognition

Collaborative content management system for musicology

Code used in the article "SATIN A Persistent Musical Database for Music Information Retrieval" by Yann Bayle, Pierre Hanna and Matthias Robine in CBMI 2017. SATIN is a MIR dataset for reproducible research.

Code to reproduce paper "Exploring Longitudinal Effects of Session-based Recommendations" in RecSys 2020

Code for the paper Musical Voice Separation as Link Prediction Modeling a Musical Perception Task as a Multi-Trajectory Tracking Problem

Code for the paper "LLark A Multimodal Foundation Model for Music" by Josh Gardner, Simon Durand, Daniel Stoller, and Rachel Bittner.

Code accompanying Applied Sciences paper titled "Assessment of Student Music Performances Using Deep Neural Networks"

Chord conditioning implemented MusicGen