SM Toolbox: MATLAB Implementations for Computing and Enhancing Similarity Matrices
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M. Müller, N. Jiang, and H. Grohganz, "SM Toolbox: MATLAB Implementations for Computing and Enhancing Similarity Matrices," Paper P2-4, (2014 January.). doi:
M. Müller, N. Jiang, and H. Grohganz, "SM Toolbox: MATLAB Implementations for Computing and Enhancing Similarity Matrices," Paper P2-4, (2014 January.). doi:
Abstract: 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.
@article{müller2014sm,
author={müller, meinard and jiang, nanzhu and grohganz, harald},
journal={journal of the audio engineering society},
title={sm toolbox: matlab implementations for computing and enhancing similarity matrices},
year={2014},
volume={},
number={},
pages={},
doi={},
month={january},}
@article{müller2014sm,
author={müller, meinard and jiang, nanzhu and grohganz, harald},
journal={journal of the audio engineering society},
title={sm toolbox: matlab implementations for computing and enhancing similarity matrices},
year={2014},
volume={},
number={},
pages={},
doi={},
month={january},
abstract={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.},}
TY - paper
TI - SM Toolbox: MATLAB Implementations for Computing and Enhancing Similarity Matrices
SP -
EP -
AU - Müller, Meinard
AU - Jiang, Nanzhu
AU - Grohganz, Harald
PY - 2014
JO - Journal of the Audio Engineering Society
IS -
VO -
VL -
Y1 - January 2014
TY - paper
TI - SM Toolbox: MATLAB Implementations for Computing and Enhancing Similarity Matrices
SP -
EP -
AU - Müller, Meinard
AU - Jiang, Nanzhu
AU - Grohganz, Harald
PY - 2014
JO - Journal of the Audio Engineering Society
IS -
VO -
VL -
Y1 - January 2014
AB - 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.
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.
Authors:
Müller, Meinard; Jiang, Nanzhu; Grohganz, Harald
Affiliations:
Universität Bonn, Bonn, Germany; International Audio Laboratories Erlangen, Erlangen, Germany(See document for exact affiliation information.)
AES Conference:
53rd International Conference: Semantic Audio (January 2014)
Paper Number:
P2-4
Publication Date:
January 27, 2014Import into BibTeX
Subject:
Audio Signal Processing and Feature Extraction
Permalink:
http://www.aes.org/e-lib/browse.cfm?elib=17092