Music Analysis, Chord Recognition, Beat Tracking, Guitar Diagrams, Piano Visualizer, Lyrics Transcription Application, context-aware LLM inference for analysis from uploaded audio and YouTube video

Automatic Chord Recognition tools - ISMIR2021 Late-Breaking Demo presentation

Ownaudio is a cross-platform C# audio library that works across platforms without external dependencies.

Android musical application with real-time chord recognition.

A Typescript port of Adam Stark's C++ implementation of the chord recognition algorithm described in the paper : Real-Time Chord Recognition For Live Performance, A. M. Stark and M. D. Plumbley.

Mobile app library for musical chord recognition and generation

Pytorch project accompanying the paper "Training Deep Pitch-Class Representations With a Multi-Label CTC Loss", ISMIR 2021.

A configurable, multi-threaded, real-time chord detector in C++ and Python.

Recognize chords in songs using Bidirectional Transformer || AI Cup 2020 - Chord Recognition Competition (9th place) / 和弦辨識競賽 (第九名)

Detects chords from midi input

extract chords from an audio file (using ohollo/chord-extractor & Chordino)

"Deep Learning Models for Automatic Chord Recognition in Polyphonic Audio” for the EPSRC-funded Bede Supercomputer studentship.

Java automatic chord recognition with neural network and digital signal processing.

This file can recognize chords or pitch by getting audio. A Tkinter UI window is created for easy use.

Repository for training chord transcription models. Achieves high-precision inference through context interpretation using the SegmentModel.

Deep Learning Model and PYPI for Automatic Chord Recognition

A lightweight MIDI plugin for midi real-time chord detection in DAWs

Keras project accompanying the paper "Learning Pitch-Class Representations from Score--Audio Pairs of Classical Music", ISMIR 2021.

Prototype AI-driven web application that analyzes and transcribes musical compositions by extracting notes and chords from audio files. The system employs advanced machine learning and audio processing techniques.

This MATLAB code creates a graph of all possible four-note chords in specified scales, performs a random walk on the graph, and outputs the results to a LaTeX file using PSTricks, which the user then compiles into an eight-page exercise in chord voicings and modulation for guitar. (See the PDF file for a completed example.)