logoMIRtoolbox offers an integrated set of functions written in Matlab, dedicated to the extraction from audio files of musical features such as tonality, rhythm, structures, etc. The objective is to offer an overview of computational approaches in the area of Music Information Retrieval. The design is based on a modular framework: the different algorithms are decomposed into stages, formalized using a minimal set of elementary mechanisms. These building blocks form the basic vocabulary of the toolbox, which can then be freely articulated in new original ways. These elementary mechanisms integrates all the different variants proposed by alternative approaches - including new strategies we have developed -, that users can select and parametrize. This synthetic digest of feature extraction tools enables a capitalization of the originality offered by all the alternative strategies. Additionally to the basic computational processes, the toolbox also includes higher-level musical feature extraction tools, whose alternative strategies, and their multiple combinations, can be selected by the user.

The choice of an object-oriented design allows a large flexibility with respect to the syntax: the tools are combined in order to form a sets of methods that correspond to basic processes (spectrum, autocorrelation, frame decomposition, etc.) and musical features. These methods can adapt to a large area of objects as input. For instance, the autocorrelation method will behave differently with audio signal or envelope, and can adapt to frame decompositions.

The toolbox was initially conceived in the context of the Brain Tuning project financed by the European Union (FP6-NEST). One main objective was to investigate the relation between musical features and music-induced emotion and the associated neural activity.

» Version 1.7 

The toolbox is available free of charge under the GNU General Public License.

This distribution actually includes, besides MIRtoolbox itself, three other toolboxes:

MIRtoolbox requires Matlab version 7 and Mathworks' Signal Processing toolbox.

» Towards MIRtoolbox 2.0 

Ten years of MIRtoolbox, time to look forward: Announcing the MiningSuite 0.9

» Authors

Olivier Lartillot, Petri Toiviainen, Pasi Saari and Tuomas Eerola were members of the Finnish Centre of Excellence in Interdisciplinary Music Research.

The development of the toolbox has benefitted from productive collaborations with the other partners of the Brain Tuning project, colleagues from research centers such as the Swiss Center for Affective Sciences, students of the MMT master program, external collaborators, active users of the toolbox, participating in particular to the discussion list, and participants of various summer schools.

» Download

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» Please Register

Please register to the MIRtoolbox announcement list. This will allow us to estimate the number of users, and this will allow you in return to get informed on the new major releases (including critical bug fixes).

» Documentation

» Discussion list

A discussion mailing list is also at your disposal:

List subscriber can send their message at the following address:


» MIRtoolbox tweets

Get informed of the day-to-day advance of the project (bug reports, bug fixes, new features, new topics, etc.) by following @mirtoolbox.

» Installation

Once the zip file has been downloaded and uncompressed, please read the instruction contained in the readme file included in the uncompressed folder.