17.05.2017

Materials for (computational) music research

MIDI Toolbox

Description

The MIDI Toolbox is a compilation of functions for analyzing and visualizing MIDI files in the Matlab computing environment (free under GNU General Public License).

Link

MIDI Toolbox

Reference

Eerola, T. & Toiviainen, P. (2004). MIDI Toolbox: MATLAB Tools for Music Research. University of Jyväskylä: Kopijyvä, Jyväskylä, Finland.

MIR Toolbox

Description

MIRtoolbox 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

Link

MIRtoolbox

Reference

Lartillot, O. & Toiviainen, P. (2007). MIR in Matlab (II): A Toolbox for Musical Feature Extraction From Audio. International Conference on Music Information Retrieval, Vienna, 2007.

MoCap Toolbox

Description

The MoCap Toolbox is a Matlab toolbox that contains functions for the analysis and visualization of motion capture data.

Link

MoCap Toolbox

Reference

Burger, B. & Toiviainen, P. (2013). MoCap Toolbox – A Matlab toolbox for computational analysis of movement data. In R. Bresin (Ed.), Proceedings of the 10th Sound and Music Computing Conference. Stockholm, Sweden: KTH Royal Institute of Technology.

WiiDataCapture

Description

WiiDataCapture is a software that displays and saves acceleration data of up to 8 Wiimotes.

Link

WiiDataCapture

 

AudioKeySOM

Description

AudioKeySOM is a software for real-time visualization of tonal content from audio. It can take various kinds of audio input, such as microphone, line-in, or an audio file. Currently, this software only runs on Macintosh computers and has been tested on Macs with an Intel processor and operating system 10.12. 

Link (zip, direct download - 136mb)

AudioKeySOM

Reference

Toiviainen, P. (2008). Visualization of tonal content in the symbolic  and audio domains. In W. B. Hewlett and E. Selfridge-Field (Eds.),  Tonal Theory for the Digital Age (Computing in Musicology 15).  Cambridge, MA: MIT Press.

 

Digital Archive of Finnish Folk Tunes

Description

Sample of 8613 Finnish folk songs in symbolic format, available in browsable format or as a Matlab data matrix with annotated meta data.

Links (zip, direct download)

Digital Archive of Finnish Folk Tunes
Collection download for research purposes (Matlab)

Reference

Eerola, T. & Toiviainen, P. (2004). Suomen Kansan eSävelmät. Suomalaisten kansansävelmien elektroninen tietovaranto [Digital Archive of Finnish Folk Tunes]. University of Jyväskylä. URL: http://esavelmat.jyu.fi