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  • Research Article
  • Open Access

Towards Structural Analysis of Audio Recordings in the Presence of Musical Variations

EURASIP Journal on Advances in Signal Processing20062007:089686

https://doi.org/10.1155/2007/89686

Received: 1 December 2005

Accepted: 13 August 2006

Published: 16 November 2006

Abstract

One major goal of structural analysis of an audio recording is to automatically extract the repetitive structure or, more generally, the musical form of the underlying piece of music. Recent approaches to this problem work well for music, where the repetitions largely agree with respect to instrumentation and tempo, as is typically the case for popular music. For other classes of music such as Western classical music, however, musically similar audio segments may exhibit significant variations in parameters such as dynamics, timbre, execution of note groups, modulation, articulation, and tempo progression. In this paper, we propose a robust and efficient algorithm for audio structure analysis, which allows to identify musically similar segments even in the presence of large variations in these parameters. To account for such variations, our main idea is to incorporate invariance at various levels simultaneously: we design a new type of statistical features to absorb microvariations, introduce an enhanced local distance measure to account for local variations, and describe a new strategy for structure extraction that can cope with the global variations. Our experimental results with classical and popular music show that our algorithm performs successfully even in the presence of significant musical variations.

Keywords

  • Tempo
  • Quantum Information
  • Efficient Algorithm
  • Recent Approach
  • Global Variation

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Authors’ Affiliations

(1)
Department of Computer Science III, University of Bonn, Bonn, Germany

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Copyright

© M. Müller and F. Kur. 2007

This article is published under license to BioMed Central Ltd. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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