Alternate Level Clustering for Drum Transcription

Abstract : This paper introduces a clustering-based unsupervised approach to the problem of drum transcription. The proposed method is based on a stack of multiple clustering and seg-mentation stages that progressively build up meaningful audio events, in a bottom-up fashion. At each level, the inherent redundancy of the repeating events guides the clustering of objects into more complex structures. Comparison with state-of-the-art approaches demonstrate the potential of the proposed approach, both in terms of efficiency and of ability to generalize.
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https://hal.archives-ouvertes.fr/hal-01122006
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  • HAL Id : hal-01122006, version 2

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Mathias Rossignol, Mathieu Lagrange, Grégoire Lafay, Emmanouil Benetos. Alternate Level Clustering for Drum Transcription. EUSIPCO, Sep 2015, Nice, France. ⟨hal-01122006v2⟩

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