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The concept of similarity matrices (SMs) has been widely used for a multitude of music analysis and retrieval tasks including audio structure analysis or version identification. For such tasks, the improvement of structural properties of the similarity matrix at an early state of the processing pipeline has turned out to be of crucial importance. In this paper, we present the SM toolbox, which contains MATLAB implementations for computing and enhancing similarity matrices in various ways. Furthermore, our toolbox includes a number of additional tools for parsing, navigation, and visualization synchronized with audio playback. Finally, we provide the code for a recently proposed audio thumbnailing procedure that demonstrates the applicability and importance of enhancement concepts. Providing MATLAB implementations on a website under a GNU-GPL license and including many illustrative examples, our aim is to foster research and education in music information retrieval.
Author (s): Müller, Meinard; Jiang, Nanzhu; Grohganz, Harald
Affiliation:
Universität Bonn, Bonn, Germany; International Audio Laboratories Erlangen, Erlangen, Germany
(See document for exact affiliation information.)
Publication Date:
2014-01-06
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Session subject:
Audio Signal Processing and Feature Extraction
Permalink: https://aes2.org/publications/elibrary-page/?id=17092
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Müller, Meinard; Jiang, Nanzhu; Grohganz, Harald; 2014; SM Toolbox: MATLAB Implementations for Computing and Enhancing Similarity Matrices [PDF]; Universität Bonn, Bonn, Germany; International Audio Laboratories Erlangen, Erlangen, Germany; Paper P2-4; Available from: https://aes2.org/publications/elibrary-page/?id=17092
Müller, Meinard; Jiang, Nanzhu; Grohganz, Harald; SM Toolbox: MATLAB Implementations for Computing and Enhancing Similarity Matrices [PDF]; Universität Bonn, Bonn, Germany; International Audio Laboratories Erlangen, Erlangen, Germany; Paper P2-4; 2014 Available: https://aes2.org/publications/elibrary-page/?id=17092