Chroma Toolbox: Pitch, Chroma, CENS, CRP

Chroma Toolbox: Pitch, Chroma, CENS, CRP

The Chroma Toolbox has been developed by Meinard Müller and Sebastian Ewert. It contains MATLAB implementations for extracting various types of novel pitch-based and chroma-based audio features. The MATLAB implementations provided on this website are published under the terms of the General Public License (GPL). A general overview of the chroma toolbox is given in [1].

If you publish results obtained using these implementations, please cite [1]. For technical details on the features please cite [2], [3], [4], [5].

Description of Pitch, Chroma, CENS, CRP features

Chroma-based audio features have turned out to be a powerful tool for various analysis tasks in Music Information Retrieval including task such as chord labeling, music summarization, structure analysis, music synchronization and audio alignment. A 12-dimensional chroma feature encodes the short-time energy distribution of the underlying music signals over the twelve chroma bands, which correspond to the twelve traditional pitch classes of the equal-tempered scale encoded by the attributes C,C#,D,D#,...,B. Such features strongly correlate to the harmonic progression of the music signal, often prominent in Western music. By identifying spectral components that differ by a musical octave, chroma features possess a significant degree of robustness to changes in timbre and instrumentation.

The Chroma Toolbox contains MATLAB implementations for the extraction of various musically meaningful features from waveform based audio signals. In particular, it contains feature extractors for pitch features as well as parameterized families of variants of chroma-like features. We quickly describe these features and refer to the literature for details. A general overview of the features and the toolbox is given in [1].


MATLAB Code

The MATLAB implementations provided on this website are published under the terms of the General Public License (GPL), version 2 or later. If you publish results obtained using these implementations, please cite the references below.

Download Chroma Toolbox (Version 2.0. Last update: 2011-08-31): [zip]

The ZIP file contains the following MATLAB files and folders:

Important Notes:


References

[1]
Meinard Müller and Sebastian Ewert
Chroma Toolbox: MATLAB Implementations for Extracting Variants of Chroma-Based Audio Features
Proceedings of the International Conference on Music Information Retrieval (ISMIR), 2011.
[bib] [pdf]
[2]
Meinard Müller
Information Retrieval for Music and Motion
Monograph, Springer, 2007.
ISBN: 978-3-540-74047-6
[bib] [link]
[3]
Meinard Müller, Frank Kurth, and Michael Clausen
Audio matching via chroma-based statistical features.
Proceedings of the International Conference on Music Information Retrieval (ISMIR), pp. 288-295, 2005.
[bib] [pdf]
[4]
Meinard Müller, Sebastian Ewert, and Sebastian Kreuzer
Making chroma features more robust to timbre changes.
Proceedings of IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Taipei, Taiwan, pp. 1869-1872, 2009.
[bib] [pdf]
[5]
Meinard Müller and Sebastian Ewert
Towards timbre-invariant audio features for harmony-based music.
IEEE Transactions on Audio, Speech, and Language Processing, vol. 18, no. 3, pp. 649–662, 2010.
[bib] [link]