Matlab implementation of the: J.R. Zapata, M. Davies and E. Gómez, "Multi-feature beat tracker," IEEE/ACM Transactions on Audio, Speech and Language Processing. 22(4), pp. 816-825, 2014"

The Panako acoustic fingerprinting system.

Synchronization tool to sync different audio captures of the same event

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

A web application that extracts and visualizes music structure. Connects with the Spotify API for audio content data.

Audio transforms for FastAI

An example AVAssetResourceLoaderDelegate implementation, with extensive sample code.

Get media information from YouTube and Vimeo videos, Spotify tracks and Discogs releases.

Instructional notebooks on music information retrieval.

Genre Classification using Convolutional Neural Networks

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

ScorePerformer: Expressive Piano Performance Rendering with Fine-Grained Control (ISMIR 2023)

Source code for "MusCaps Generating Captions for Music Audio" (IJCNN 2021)

List of academic resources on Multimodal ML for Music

Official implementation of "Contrastive Audio-Language Learning for Music" (ISMIR 2022)

Structured Data from Ishkur's Guide to Electronic Music. Working Mirror for v2.5 here: https://igorbrigadir.github.io/ishkurs-guide-dataset/

This repository contains a web application that integrates with a music recommendation system, which leverages a dataset of 3,415 audio files, each lasting thirty seconds, utilising a Locality-Sensitive Hashing (LSH) implementation to determine rhythmic similarity, as part of an assignment for the Fundamental of Big Data Analytics (DS2004) course.

[REPO] Create a music genre dataset (metadata or audio) for classification using the Spotify Web API

Open source library that allows you to efficiently compute audio features.

A CNN which converts piano audio to a simplified MIDI format

USB Audio DAC using inexpensive STM32F411 / 401 "Black Pill" and PCM5102A modules

AudioLDM training, finetuning, evaluation and inference.

FPGA based USB 2.0 high speed audio interface featuring multiple optical ADAT inputs and outputs

Basics of Musical Instruments Classification using Machine Learning

Code for Vision-Infused Deep Audio Inpainting (ICCV 2019)

the dataset used in the paper https://drive.google.com/file/d/0B4bIMgQlCAuqdGVRbVNNbzJfeUU/view

Audio Coding Notebooks and Tutorials

Lyrics-to-audio-alignement system. Based on Machine Learning Algorithms: Hidden Markov Models with Viterbi forced alignment. The alignment is explicitly aware of durations of musical notes. The phonetic model are classified with MLP Deep Neural Network.

A data framework for music information retrieval focusing on electronic music.

Control mechanisms to the U-Net architecture for doing multiple source separation instruments