The general music learning public places a high demand on chord-based representations of popular music, as evidenced by large online communities surrounding websites like e-chords or Ultimate Guitar. Given the prerequisite skill necessary to manually identify chords from recorded audio, there is considerable motivation to develop automated systems capable of reliably performing this task. The goal of automatic chord estimation research is to develop systems that produce time-aligned sequences of chords from a given music signal.
Source Code
The source code for this project can be found on github.
Related Publications
Four Timely Insights on Automatic Chord Recognition
E. Humphrey, J.P. Bello
Four Timely Insights on Automatic Chord Recognition
ISMIR 2015, Malaga, Spain. October 2015
An Exploration of Deep Learning in Content-Based Music Informatics
Eric J. Humphrey
An Exploration of Deep Learning in Content-Based Music Informatics
Ph.D. Thesis, New York University, New York, NY, 2015
From music audio to chord tablature: Teaching deep convolutional networks to play guitar
E.J. Humphrey, J.P. Bello
From music audio to chord tablature: Teaching deep convolutional networks to play guitar
ICASSP, Florence, Italy, May 2014
On the relative importance of individual components of chord recognition systems
T. Cho, J.P. Bello
On the relative importance of individual components of chord recognition systems
IEEE Transactions on Audio, Speech, and Language Processing, Feb. 2014
Improved Techniques for Automatic Chord Recognition from Music Audio Signals
T. Cho
Improved Techniques for Automatic Chord Recognition from Music Audio Signals
Ph.D. Thesis, New York University, New York NY, 2013
Rethinking Automatic Chord Recognition with Convolutional Neural Networks
E. Humphrey, J.P. Bello
Rethinking Automatic Chord Recognition with Convolutional Neural Networks
Proceedings of the 11th International Conference on Machine Learning and Applications (ICMLA-12), Boca Raton, FL, USA. December. 2012
Learning a robust tonnetz-space transform for automatic chord recognition
E.J. Humphrey, T. Cho, J.P. Bello
Learning a robust tonnetz-space transform for automatic chord recognition
Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP-12) Kyoto, Japan, May 2012
A Feature Smoothing Method for Chord Recognition Using Recurrence Plots
T. Cho, J.P. Bello
A Feature Smoothing Method for Chord Recognition Using Recurrence Plots
Proceedings of the 12th International Society for Music Information Retrieval, (ISMIR 2011) Miami, FL., USA, oct 2011
Exploring common variations in state of the art chord recognition systems
T. Cho, R.J. Weiss, J.P. Bello
Exploring common variations in state of the art chord recognition systems
Proceedings of the Sound and Music Computing Conference (SMC) Barcelona, Spain, Jul 2010