The CoMIRVA toolkit for visualizing music-related data

  • Authors:

  • Markus Schedl;Peter Knees;Klaus Seyerlehner;Tim Pohle

  • Affiliations:

  • Department of Computational Perception, Johannes Kepler University Linz, Austria;Department of Computational Perception, Johannes Kepler University Linz, Austria;Department of Computational Perception, Johannes Kepler University Linz, Austria;Department of Computational Perception, Johannes Kepler University Linz, Austria

  • Venue:
  • EUROVIS'07 Proceedings of the 9th Joint Eurographics / IEEE VGTC conference on Visualization
  • Year:
  • 2007

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Abstract

We present CoMIRVA, which is an abbreviation for Collection of Music Information Retrieval and Visualization Applications. CoMIRVA is a Java framework and toolkit for information retrieval and visualization. It is licensed under the GNU GPL and can be downloaded from http://www.cp.jku.at/comirva/. At the moment, the main functionalities include music information retrieval, web retrieval, and visualization of the extracted information. In this paper, we focus on the visualization aspects of CoMIRVA. Since many of the information retrieval functions are intended to be applied to problems of the field of music information retrieval (MIR), we demonstrate the functions using data like similarity matrices of music artists gained by analyzing artist-related web pages. CoMIRVA is continuously being extended. Currently, it supports the following visualization techniques: Self-Organizing Map, Smoothed Data Histogram, Circled Bars, Circled Fans, Probabilistic Network, Continuous Similarity Ring, Sunburst, and Music Description Map. Since space is limited, we can only present a selected number of these in this paper. As one key feature of CoMIRVA is its easy extensibility, we further elaborate on how CoMIRVA was used for creating a novel user interface to digital music repositories.