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2012
Conference Paper
Titel

Improved music similarity computation based on tone objects

Abstract
In this paper, we propose a novel approach for music similarity estimation. It combines temporal segmentation of music signals with source separation into so-called tone objects. We solely use the timbre-related audio features Mel- Frequency Cepstral Coefficients (MFCC) and Octave-based Spectral Contrast (OSC) to describe the extracted tone objects. First, we compare our approach to a baseline system that employs frame-wise feature extraction and bagof- frames classification. Second, we set up a system that extracts features on perfectly isolated single track recordings, achieving near perfect classification. Finally, we compare our novel approach against the basis experiments. We find that it clearly outperforms the baseline system in a fiveclass genre classification task. Our results indicate that tone object based feature extraction clearly improves music similarity estimation.
Author(s)
Krasser, Johannes
Abeßer, Jakob
Cano, E.
Dittmar, C.
Großmann, H.
Hauptwerk
7th Audio Mostly Conference on A Conference on Interaction with Sound, AM 2012. Proceedings
Konferenz
Audio Mostly Conference 2012
Thumbnail Image
DOI
10.1145/2371456.2371464
Language
English
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Fraunhofer-Institut für Digitale Medientechnologie IDMT
Tags
  • audio similarity

  • genre classification

  • harmonic-percussive decomposition

  • multitrack recordings

  • tone objects

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